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.

Mixed-up trees: the structure of phylogenetic mixtures.

PubMed

Matsen, Frederick A; Mossel, Elchanan; Steel, Mike

2008-05-01

In this paper, we apply new geometric and combinatorial methods to the study of phylogenetic mixtures. The focus of the geometric approach is to describe the geometry of phylogenetic mixture distributions for the two state random cluster model, which is a generalization of the two state symmetric (CFN) model. In particular, we show that the set of mixture distributions forms a convex polytope and we calculate its dimension; corollaries include a simple criterion for when a mixture of branch lengths on the star tree can mimic the site pattern frequency vector of a resolved quartet tree. Furthermore, by computing volumes of polytopes we can clarify how "common" non-identifiable mixtures are under the CFN model. We also present a new combinatorial result which extends any identifiability result for a specific pair of trees of size six to arbitrary pairs of trees. Next we present a positive result showing identifiability of rates-across-sites models. Finally, we answer a question raised in a previous paper concerning "mixed branch repulsion" on trees larger than quartet trees under the CFN model.

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

PubMed

Tan, Yin-Yin Sarah; Mueller, Shane T

2016-09-01

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

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Spatial pattern affects diversity-productivity relationships in experimental meadow communities

NASA Astrophysics Data System (ADS)

Lamošová, Tereza; Doležal, Jiří; Lanta, Vojtěch; Lepš, Jan

2010-05-01

Plant species create aggregations of conspecifics as a consequence of limited seed dispersal, clonal growth and heterogeneous environment. Such intraspecific aggregation increases the importance of intraspecific competition relative to interspecific competition which may slow down competitive exclusion and promote species coexistence. To examine how spatial aggregation impacts the functioning of experimental assemblages of varying species richness, eight perennial grassland species of different growth form were grown in random and aggregated patterns in monocultures, two-, four-, and eight-species mixtures. In mixtures with an aggregated pattern, monospecific clumps were interspecifically segregated. Mixed model ANOVA was used to test (i) how the total productivity and productivity of individual species is affected by the number of species in a mixture, and (ii) how these relationships are affected by spatial pattern of sown plants. The main patterns of productivity response to species richness conform to other studies: non-transgressive overyielding is omnipresent (the productivity of mixtures is higher than the average of its constituent species so that the net diversity, selection and complementarity effects are positive), whereas transgressive overyielding is found only in a minority of cases (average of log(overyielding) being close to zero or negative). The theoretical prediction that plants in a random pattern should produce more than in an aggregated pattern (the distances to neighbours are smaller and consequently the competition among neighbours stronger) was confirmed in monocultures of all the eight species. The situation is more complicated in mixtures, probably as a consequence of complicated interplay between interspecific and intraspecific competition. The most productive species ( Achillea, Holcus, Plantago) were competitively superior and increased their relative productivity with mixture richness. The intraspecific competition of these species is stronger than that of most other species. The aggregated pattern in the full mixture increased the survival of subordinate species, and consequently, we conclude that an aggregated pattern can promote species coexistence (or at least postpone competitive exclusion), particularly in comparison with homogeneously sown mixtures.

Prospective aquatic risk assessment for chemical mixtures in agricultural landscapes

PubMed Central

Brown, Colin D.; Hamer, Mick; Jones, Russell; Maltby, Lorraine; Posthuma, Leo; Silberhorn, Eric; Teeter, Jerold Scott; Warne, Michael St J; Weltje, Lennart

2018-01-01

Abstract Environmental risk assessment of chemical mixtures is challenging because of the multitude of possible combinations that may occur. Aquatic risk from chemical mixtures in an agricultural landscape was evaluated prospectively in 2 exposure scenario case studies: at field scale for a program of 13 plant‐protection products applied annually for 20 yr and at a watershed scale for a mixed land‐use scenario over 30 yr with 12 plant‐protection products and 2 veterinary pharmaceuticals used for beef cattle. Risk quotients were calculated from regulatory exposure models with typical real‐world use patterns and regulatory acceptable concentrations for individual chemicals. The results could differentiate situations when there was concern associated with single chemicals from those when concern was associated with a mixture (based on concentration addition) with no single chemical triggering concern. Potential mixture risk was identified on 0.02 to 7.07% of the total days modeled, depending on the scenario, the taxa, and whether considering acute or chronic risk. Taxa at risk were influenced by receiving water body characteristics along with chemical use profiles and associated properties. The present study demonstrates that a scenario‐based approach can be used to determine whether mixtures of chemicals pose risks over and above any identified using existing approaches for single chemicals, how often and to what magnitude, and ultimately which mixtures (and dominant chemicals) cause greatest concern. Environ Toxicol Chem 2018;37:674–689. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. PMID:29193235

Prospective aquatic risk assessment for chemical mixtures in agricultural landscapes.

PubMed

Holmes, Christopher M; Brown, Colin D; Hamer, Mick; Jones, Russell; Maltby, Lorraine; Posthuma, Leo; Silberhorn, Eric; Teeter, Jerold Scott; Warne, Michael St J; Weltje, Lennart

2018-03-01

Environmental risk assessment of chemical mixtures is challenging because of the multitude of possible combinations that may occur. Aquatic risk from chemical mixtures in an agricultural landscape was evaluated prospectively in 2 exposure scenario case studies: at field scale for a program of 13 plant-protection products applied annually for 20 yr and at a watershed scale for a mixed land-use scenario over 30 yr with 12 plant-protection products and 2 veterinary pharmaceuticals used for beef cattle. Risk quotients were calculated from regulatory exposure models with typical real-world use patterns and regulatory acceptable concentrations for individual chemicals. The results could differentiate situations when there was concern associated with single chemicals from those when concern was associated with a mixture (based on concentration addition) with no single chemical triggering concern. Potential mixture risk was identified on 0.02 to 7.07% of the total days modeled, depending on the scenario, the taxa, and whether considering acute or chronic risk. Taxa at risk were influenced by receiving water body characteristics along with chemical use profiles and associated properties. The present study demonstrates that a scenario-based approach can be used to determine whether mixtures of chemicals pose risks over and above any identified using existing approaches for single chemicals, how often and to what magnitude, and ultimately which mixtures (and dominant chemicals) cause greatest concern. Environ Toxicol Chem 2018;37:674-689. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Individual and binary toxicity of anatase and rutile nanoparticles towards Ceriodaphnia dubia.

PubMed

Iswarya, V; Bhuvaneshwari, M; Chandrasekaran, N; Mukherjee, Amitava

2016-09-01

Increasing usage of engineered nanoparticles, especially Titanium dioxide (TiO2) in various commercial products has necessitated their toxicity evaluation and risk assessment, especially in the aquatic ecosystem. In the present study, a comprehensive toxicity assessment of anatase and rutile NPs (individual as well as a binary mixture) has been carried out in a freshwater matrix on Ceriodaphnia dubia under different irradiation conditions viz., visible and UV-A. Anatase and rutile NPs produced an LC50 of about 37.04 and 48mg/L, respectively, under visible irradiation. However, lesser LC50 values of about 22.56 (anatase) and 23.76 (rutile) mg/L were noted under UV-A irradiation. A toxic unit (TU) approach was followed to determine the concentrations of binary mixtures of anatase and rutile. The binary mixture resulted in an antagonistic and additive effect under visible and UV-A irradiation, respectively. Among the two different modeling approaches used in the study, Marking-Dawson model was noted to be a more appropriate model than Abbott model for the toxicity evaluation of binary mixtures. The agglomeration of NPs played a significant role in the induction of antagonistic and additive effects by the mixture based on the irradiation applied. TEM and zeta potential analysis confirmed the surface interactions between anatase and rutile NPs in the mixture. Maximum uptake was noticed at 0.25 total TU of the binary mixture under visible irradiation and 1 TU of anatase NPs for UV-A irradiation. Individual NPs showed highest uptake under UV-A than visible irradiation. In contrast, binary mixture showed a difference in the uptake pattern based on the type of irradiation exposed. Copyright © 2016 Elsevier B.V. All rights reserved.

Foam patterns

DOEpatents

Chaudhry, Anil R; Dzugan, Robert; Harrington, Richard M; Neece, Faurice D; Singh, Nipendra P; Westendorf, Travis

2013-11-26

A method of creating a foam pattern comprises mixing a polyol component and an isocyanate component to form a liquid mixture. The method further comprises placing a temporary core having a shape corresponding to a desired internal feature in a cavity of a mold and inserting the mixture into the cavity of the mold so that the mixture surrounds a portion of the temporary core. The method optionally further comprises using supporting pins made of foam to support the core in the mold cavity, with such pins becoming integral part of the pattern material simplifying subsequent processing. The method further comprises waiting for a predetermined time sufficient for a reaction from the mixture to form a foam pattern structure corresponding to the cavity of the mold, wherein the foam pattern structure encloses a portion of the temporary core and removing the temporary core from the pattern independent of chemical leaching.

Larval aquatic insect responses to cadmium and zinc in experimental streams.

PubMed

Mebane, Christopher A; Schmidt, Travis S; Balistrieri, Laurie S

2017-03-01

To evaluate the risks of metal mixture effects to natural stream communities under ecologically relevant conditions, the authors conducted 30-d tests with benthic macroinvertebrates exposed to cadmium (Cd) and zinc (Zn) in experimental streams. The simultaneous exposures were with Cd and Zn singly and with Cd+Zn mixtures at environmentally relevant ratios. The tests produced concentration-response patterns that for individual taxa were interpreted in the same manner as classic single-species toxicity tests and for community metrics such as taxa richness and mayfly (Ephemeroptera) abundance were interpreted in the same manner as with stream survey data. Effect concentrations from the experimental stream exposures were usually 2 to 3 orders of magnitude lower than those from classic single-species tests. Relative to a response addition model, which assumes that the joint toxicity of the mixtures can be predicted from the product of their responses to individual toxicants, the Cd+Zn mixtures generally showed slightly less than additive toxicity. The authors applied a modeling approach called Tox to explore the mixture toxicity results and to relate the experimental stream results to field data. The approach predicts the accumulation of toxicants (hydrogen, Cd, and Zn) on organisms using a 2-pK a bidentate model that defines interactions between dissolved cations and biological receptors (biotic ligands) and relates that accumulation through a logistic equation to biological response. The Tox modeling was able to predict Cd+Zn mixture responses from the single-metal exposures as well as responses from field data. The similarity of response patterns between the 30-d experimental stream tests and field data supports the environmental relevance of testing aquatic insects in experimental streams. Environ Toxicol Chem 2017;36:749-762. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

NASA Astrophysics Data System (ADS)

Lee, Sanggyun; Kim, Hyun-cheol; Im, Jungho

2018-05-01

We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m) MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0), as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011-2016, excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

Flow Pattern Phenomena in Two-Phase Flow in Microchannels

NASA Astrophysics Data System (ADS)

Keska, Jerry K.; Simon, William E.

2004-02-01

Space transportation systems require high-performance thermal protection and fluid management techniques for systems ranging from cryogenic fluid management devices to primary structures and propulsion systems exposed to extremely high temperatures, as well as for other space systems such as cooling or environment control for advanced space suits and integrated circuits. Although considerable developmental effort is being expended to bring potentially applicable technologies to a readiness level for practical use, new and innovative methods are still needed. One such method is the concept of Advanced Micro Cooling Modules (AMCMs), which are essentially compact two-phase heat exchangers constructed of microchannels and designed to remove large amounts of heat rapidly from critical systems by incorporating phase transition. The development of AMCMs requires fundamental technological advancement in many areas, including: (1) development of measurement methods/systems for flow-pattern measurement/identification for two-phase mixtures in microchannels; (2) development of a phenomenological model for two-phase flow which includes the quantitative measure of flow patterns; and (3) database development for multiphase heat transfer/fluid dynamics flows in microchannels. This paper focuses on the results of experimental research in the phenomena of two-phase flow in microchannels. The work encompasses both an experimental and an analytical approach to incorporating flow patterns for air-water mixtures flowing in a microchannel, which are necessary tools for the optimal design of AMCMs. Specifically, the following topics are addressed: (1) design and construction of a sensitive test system for two-phase flow in microchannels, one which measures ac and dc components of in-situ physical mixture parameters including spatial concentration using concomitant methods; (2) data acquisition and analysis in the amplitude, time, and frequency domains; and (3) analysis of results including evaluation of data acquisition techniques and their validity for application in flow pattern determination.

A feasibility study on estimation of tissue mixture contributions in 3D arterial spin labeling sequence

NASA Astrophysics Data System (ADS)

Liu, Yang; Pu, Huangsheng; Zhang, Xi; Li, Baojuan; Liang, Zhengrong; Lu, Hongbing

2017-03-01

Arterial spin labeling (ASL) provides a noninvasive measurement of cerebral blood flow (CBF). Due to relatively low spatial resolution, the accuracy of CBF measurement is affected by the partial volume (PV) effect. To obtain accurate CBF estimation, the contribution of each tissue type in the mixture is desirable. In general, this can be obtained according to the registration of ASL and structural image in current ASL studies. This approach can obtain probability of each tissue type inside each voxel, but it also introduces error, which include error of registration algorithm and imaging itself error in scanning of ASL and structural image. Therefore, estimation of mixture percentage directly from ASL data is greatly needed. Under the assumption that ASL signal followed the Gaussian distribution and each tissue type is independent, a maximum a posteriori expectation-maximization (MAP-EM) approach was formulated to estimate the contribution of each tissue type to the observed perfusion signal at each voxel. Considering the sensitivity of MAP-EM to the initialization, an approximately accurate initialization was obtain using 3D Fuzzy c-means method. Our preliminary results demonstrated that the GM and WM pattern across the perfusion image can be sufficiently visualized by the voxel-wise tissue mixtures, which may be promising for the diagnosis of various brain diseases.

Processing of odor mixtures in the zebrafish olfactory bulb.

PubMed

Tabor, Rico; Yaksi, Emre; Weislogel, Jan-Marek; Friedrich, Rainer W

2004-07-21

Components of odor mixtures often are not perceived individually, suggesting that neural representations of mixtures are not simple combinations of the representations of the components. We studied odor responses to binary mixtures of amino acids and food extracts at different processing stages in the olfactory bulb (OB) of zebrafish. Odor-evoked input to the OB was measured by imaging Ca2+ signals in afferents to olfactory glomeruli. Activity patterns evoked by mixtures were predictable within narrow limits from the component patterns, indicating that mixture interactions in the peripheral olfactory system are weak. OB output neurons, the mitral cells (MCs), were recorded extra- and intracellularly and responded to odors with stimulus-dependent temporal firing rate modulations. Responses to mixtures of amino acids often were dominated by one of the component responses. Responses to mixtures of food extracts, in contrast, were more distinct from both component responses. These results show that mixture interactions can result from processing in the OB. Moreover, our data indicate that mixture interactions in the OB become more pronounced with increasing overlap of input activity patterns evoked by the components. Emerging from these results are rules of mixture interactions that may explain behavioral data and provide a basis for understanding the processing of natural odor stimuli in the OB.

Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction

NASA Astrophysics Data System (ADS)

Hansen, Matthew; Everett, Logan; Singh, Larry; Hannenhalli, Sridhar

Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation. Here we present a novel mixture modeling approach where a TF-Gene pair is presumed to be significantly correlated (with unknown coefficient) in a (unknown) subset of expression samples. The parameters of the model are estimated using a Maximum Likelihood approach. The estimated mixture of expression samples is then mined to identify genes potentially modulating the TF-Gene interaction. We have validated our approach using synthetic data and on three biological cases in cow and in yeast. While limited in some ways, as discussed, the work represents a novel approach to mine expression data and detect potential modulators of regulatory interactions.

A novel expert system for objective masticatory efficiency assessment

PubMed Central

2018-01-01

Most of the tools and diagnosis models of Masticatory Efficiency (ME) are not well documented or severely limited to simple image processing approaches. This study presents a novel expert system for ME assessment based on automatic recognition of mixture patterns of masticated two-coloured chewing gums using a combination of computational intelligence and image processing techniques. The hypotheses tested were that the proposed system could accurately relate specimens to the number of chewing cycles, and that it could identify differences between the mixture patterns of edentulous individuals prior and after complete denture treatment. This study enrolled 80 fully-dentate adults (41 females and 39 males, 25 ± 5 years of age) as the reference population; and 40 edentulous adults (21 females and 19 males, 72 ± 8.9 years of age) for the testing group. The system was calibrated using the features extracted from 400 samples covering 0, 10, 15, and 20 chewing cycles. The calibrated system was used to automatically analyse and classify a set of 160 specimens retrieved from individuals in the testing group in two appointments. The ME was then computed as the predicted number of chewing strokes that a healthy reference individual would need to achieve a similar degree of mixture measured against the real number of cycles applied to the specimen. The trained classifier obtained a Mathews Correlation Coefficient score of 0.97. ME measurements showed almost perfect agreement considering pre- and post-treatment appointments separately (κ ≥ 0.95). Wilcoxon signed-rank test showed that a complete denture treatment for edentulous patients elicited a statistically significant increase in the ME measurements (Z = -2.31, p < 0.01). We conclude that the proposed expert system proved able and reliable to accurately identify patterns in mixture and provided useful ME measurements. PMID:29385165

On selecting a prior for the precision parameter of Dirichlet process mixture models

USGS Publications Warehouse

Dorazio, R.M.

2009-01-01

In hierarchical mixture models the Dirichlet process is used to specify latent patterns of heterogeneity, particularly when the distribution of latent parameters is thought to be clustered (multimodal). The parameters of a Dirichlet process include a precision parameter ?? and a base probability measure G0. In problems where ?? is unknown and must be estimated, inferences about the level of clustering can be sensitive to the choice of prior assumed for ??. In this paper an approach is developed for computing a prior for the precision parameter ?? that can be used in the presence or absence of prior information about the level of clustering. This approach is illustrated in an analysis of counts of stream fishes. The results of this fully Bayesian analysis are compared with an empirical Bayes analysis of the same data and with a Bayesian analysis based on an alternative commonly used prior.

Patterned graphene functionalization via mask-free scanning of micro-plasma jet under ambient condition

NASA Astrophysics Data System (ADS)

Ye, Dong; Wu, Shu-Qun; Yu, Yao; Liu, Lin; Lu, Xin-Pei; Wu, Yue

2014-03-01

In this work, a mask-free method is introduced for patterned nitrogen doping of graphene using a micro-plasma jet under ambient condition. Raman and X-ray photoelectron spectroscopy spectra indicate that nitrogen atoms are incorporated into the graphene lattice with the two-dimensional spatial distribution precisely controlled in the range of mm down to 10 μm. Since the chemistry of the micro-plasma jet can be controlled by the choice of the gas mixture, this direct writing process with micro-plasma jet can be a versatile approach for patterned functionalization of graphene with high spatial resolution. This could have promising applications in graphene-based electronics.

Glomerular Activity Patterns Evoked by Natural Odor Objects in the Rat Olfactory Bulb Are Related to Patterns Evoked by Major Odorant Components

PubMed Central

Johnson, Brett A.; Ong, Joan; Leon, Michael

2014-01-01

To determine how responses evoked by natural odorant mixtures compare to responses evoked by individual odorant chemicals, we mapped 2-deoxyglucose uptake during exposures to vapors arising from a variety of odor objects that may be important to rodents in the wild. We studied 21 distinct natural odor stimuli ranging from possible food sources such as fruits, vegetables, and meats to environmental odor objects such as grass, herbs, and tree leaves. The natural odor objects evoked robust and surprisingly focal patterns of 2-deoxyglucose uptake involving clusters of neighboring glomeruli, thereby resembling patterns evoked by pure chemicals. Overall, the patterns were significantly related to patterns evoked by monomolecular odorant components that had been studied previously. Object patterns also were significantly related to the molecular features present in the mixture components. Despite these overall relationships, there were individual examples of object patterns that were simpler than might have been predicted given the multiplicity of components present in the vapors. In these cases, the object patterns lacked certain responses evoked by their major odorant mixture components. These data suggest the possibility of mixture response interactions and provide a foundation for understanding the neural coding of natural odor stimuli. PMID:20187145

Quantification of the fraction poorly deformable red blood cells using ektacytometry.

PubMed

Streekstra, G J; Dobbe, J G G; Hoekstra, A G

2010-06-21

We describe a method to obtain the fraction of poorly deformable red blood cells in a blood sample from the intensity pattern in an ektacytometer. In an ektacytometer red blood cells are transformed into ellipsoids by a shear flow between two transparent cylinders. The intensity pattern, due to a laser beam that is sent through the suspension, is projected on a screen. When measuring a healthy red blood cell population iso-intensity curves are ellipses with an axial ratio equal to that of the average red blood cell. In contrast poorly deformable cells result in circular iso-intensity curves. In this study we show that for mixtures of deformable and poorly deformable red blood cells, iso-intensity curves in the composite intensity pattern are neither elliptical nor circular but obtain cross-like shapes. We propose a method to obtain the fraction of poorly deformable red blood cells from those intensity patterns. Experiments with mixtures of poorly deformable and deformable red blood cells validate the method and demonstrate its accuracy. In a clinical setting our approach is potentially of great value for the detection of the fraction of sickle cells in blood samples of patients with sickle cell disease or to find a measure for the parasitemia in patients infected with malaria.

Kinetic theory of pattern formation in mixtures of microtubules and molecular motors

NASA Astrophysics Data System (ADS)

Maryshev, Ivan; Marenduzzo, Davide; Goryachev, Andrew B.; Morozov, Alexander

2018-02-01

In this study we formulate a theoretical approach, based on a Boltzmann-like kinetic equation, to describe pattern formation in two-dimensional mixtures of microtubular filaments and molecular motors. Following the previous work by Aranson and Tsimring [Phys. Rev. E 74, 031915 (2006), 10.1103/PhysRevE.74.031915] we model the motor-induced reorientation of microtubules as collision rules, and devise a semianalytical method to calculate the corresponding interaction integrals. This procedure yields an infinite hierarchy of kinetic equations that we terminate by employing a well-established closure strategy, developed in the pattern-formation community and based on a power-counting argument. We thus arrive at a closed set of coupled equations for slowly varying local density and orientation of the microtubules, and study its behavior by performing a linear stability analysis and direct numerical simulations. By comparing our method with the work of Aranson and Tsimring, we assess the validity of the assumptions required to derive their and our theories. We demonstrate that our approximation-free evaluation of the interaction integrals and our choice of a systematic closure strategy result in a rather different dynamical behavior than was previously reported. Based on our theory, we discuss the ensuing phase diagram and the patterns observed.

Photolithography and Fluorescence Correlation Spectroscopy used to examine the rates of exchange in reverse micelle systems

NASA Astrophysics Data System (ADS)

Norris, Zach; Mawson, Cara; Johnson, Kyron; Kessler, Sarah; Rebecca, Anne; Wolf, Nathan; Lim, Michael; Nucci, Nathaniel

Reverse micelles are molecular complexes that encapsulate a nanoscale pool of water in a surfactant shell dissolved in non-polar solvent. These complexes have a wide range of applications, and in all cases, the degree to which reverse micelles (RM) exchange their contents is relevant for their use. Despite its importance, this aspect of RM behavior is poorly understood. Photolithography is employed here to create micro and nano scale fluidic systems in which mixing rates can be precisely measured using fluorescence correlation spectroscopy (FCS). Micro-channel patterns are etched using reactive ion etching process into a layer of silicon dioxide on crystalline silicon substrates. Solutions containing mixtures of reverse micelles, proteins, and fluorophores are placed into reservoirs in the patterns, while diffusion and exchange between RMs is monitored using a FCS system built from a modified confocal Raman spectrometer. Using this approach, the diffusion and exchange rates for RM systems are measured as a function of the components of the RM mixture. Funding provided by Rowan University.

Quantile regression in the presence of monotone missingness with sensitivity analysis

PubMed Central

Liu, Minzhao; Daniels, Michael J.; Perri, Michael G.

2016-01-01

In this paper, we develop methods for longitudinal quantile regression when there is monotone missingness. In particular, we propose pattern mixture models with a constraint that provides a straightforward interpretation of the marginal quantile regression parameters. Our approach allows sensitivity analysis which is an essential component in inference for incomplete data. To facilitate computation of the likelihood, we propose a novel way to obtain analytic forms for the required integrals. We conduct simulations to examine the robustness of our approach to modeling assumptions and compare its performance to competing approaches. The model is applied to data from a recent clinical trial on weight management. PMID:26041008

A novel approach to fabricate dye-encapsulated polymeric micro- and nanoparticles by thin film dewetting technique.

PubMed

Chatterjee, Manosree; Hens, Abhiram; Mahato, Kuldeep; Jaiswal, Namita; Mahato, Nivedita; Nagahanumaiah; Chanda, Nripen

2017-11-15

A new method is reported for fabrication of polymeric micro- and nanoparticles from an intermediate patterned surface originated by dewetting of a polymeric thin film. Poly (d, l-lactide-co-glycolide) or PLGA, a biocompatible polymer is used to develop a thin film over a clean glass substrate which dewets spontaneously in the micro-/nano-patterned surface of size range 50nm to 3.5µm. Since another water-soluble polymer, poly vinyl alcohol (PVA) is coated on the same glass substrate before PLGA thin film formation, developed micro-/nano-patterns are easily extracted in water in the form of micro- and nanoparticle mixture of size range 50nm to 3.0µm. This simplified method is also used to effectively encapsulate a dye molecule, rhodamine B inside the PLGA micro-/nanoparticles. The developed dye-encapsulated nanoparticles, PLGA-rhodamine are separated from the mixture and tested for in-vitro delivery application of external molecules inside human lung cancer cells. For the first time, the use of thin film dewetting technique is reported as a potential route for the synthesis of polymeric micro-/nanoparticles and effective encapsulation of external species therein. Copyright © 2017 Elsevier Inc. All rights reserved.

Discovering Condition-Specific Gene Co-Expression Patterns Using Gaussian Mixture Models: A Cancer Case Study.

PubMed

Ficklin, Stephen P; Dunwoodie, Leland J; Poehlman, William L; Watson, Christopher; Roche, Kimberly E; Feltus, F Alex

2017-08-17

A gene co-expression network (GCN) describes associations between genes and points to genetic coordination of biochemical pathways. However, genetic correlations in a GCN are only detectable if they are present in the sampled conditions. With the increasing quantity of gene expression samples available in public repositories, there is greater potential for discovery of genetic correlations from a variety of biologically interesting conditions. However, even if gene correlations are present, their discovery can be masked by noise. Noise is introduced from natural variation (intrinsic and extrinsic), systematic variation (caused by sample measurement protocols and instruments), and algorithmic and statistical variation created by selection of data processing tools. A variety of published studies, approaches and methods attempt to address each of these contributions of variation to reduce noise. Here we describe an approach using Gaussian Mixture Models (GMMs) to address natural extrinsic (condition-specific) variation during network construction from mixed input conditions. To demonstrate utility, we build and analyze a condition-annotated GCN from a compendium of 2,016 mixed gene expression data sets from five tumor subtypes obtained from The Cancer Genome Atlas. Our results show that GMMs help discover tumor subtype specific gene co-expression patterns (modules) that are significantly enriched for clinical attributes.

Regional patterns of pesticide concentrations in surface waters of New York in 1997

USGS Publications Warehouse

Phillips, P.J.; Eckhardt, D.A.; Freehafer, D.A.; Wall, G.R.; Ingleston, H.H.

2002-01-01

The predominant mixtures of pesticides found in New York surface waters consist of five principal components. First, herbicides commonly used on corn (atrazine, metolachlor, alachlor, cyanazine) and a herbicide degradate (deethylatrazine) were positively correlated to a corn-herbicide component, and watersheds with the highest corn-herbicide component scores were those in which large amounts of row crops are grown. Second, two insecticides (diazinon and carbaryl) and one herbicide (prometon) widely used in urban and residential settings were positively correlated to an urban/residential component. Watersheds with the highest urban/residential component scores were those with large amounts of urban and residential land use. A third component was related to two herbicides (EPTC and cyanazine) used on dry beans and corn, the fourth to an herbicide (simazine) and an insecticide (carbaryl) commonly used in orchards and vineyards, and the fifth to an herbicide (DCPA). Results of this study indicate that this approach can be used to: (1) identify common mixtures of pesticides in surface waters, (2) relate these mixtures to land use and pesticide applications, and (3) indicate regions where these mixtures of pesticides are commonly found.

A mixture toxicity approach to predict the toxicity of Ag decorated ZnO nanomaterials.

PubMed

Azevedo, S L; Holz, T; Rodrigues, J; Monteiro, T; Costa, F M; Soares, A M V M; Loureiro, S

2017-02-01

Nanotechnology is a rising field and nanomaterials can now be found in a vast variety of products with different chemical compositions, sizes and shapes. New nanostructures combining different nanomaterials are being developed due to their enhancing characteristics when compared to nanomaterials alone. In the present study, the toxicity of a nanostructure composed by a ZnO nanomaterial with Ag nanomaterials on its surface (designated as ZnO/Ag nanostructure) was assessed using the model-organism Daphnia magna and its toxicity predicted based on the toxicity of the single components (Zn and Ag). For that ZnO and Ag nanomaterials as single components, along with its mixture prepared in the laboratory, were compared in terms of toxicity to ZnO/Ag nanostructures. Toxicity was assessed by immobilization and reproduction tests. A mixture toxicity approach was carried out using as starting point the conceptual model of Concentration Addition. The laboratory mixture of both nanomaterials showed that toxicity was dependent on the doses of ZnO and Ag used (immobilization) or presented a synergistic pattern (reproduction). The ZnO/Ag nanostructure toxicity prediction, based on the percentage of individual components, showed an increase in toxicity when compared to the expected (immobilization) and dependent on the concentration used (reproduction). This study demonstrates that the toxicity of the prepared mixture of ZnO and Ag and of the ZnO/Ag nanostructure cannot be predicted based on the toxicity of their components, highlighting the importance of taking into account the interaction between nanomaterials when assessing hazard and risk. Copyright © 2016 Elsevier B.V. All rights reserved.

Style consistent classification of isogenous patterns.

PubMed

Sarkar, Prateek; Nagy, George

2005-01-01

In many applications of pattern recognition, patterns appear together in groups (fields) that have a common origin. For example, a printed word is usually a field of character patterns printed in the same font. A common origin induces consistency of style in features measured on patterns. The features of patterns co-occurring in a field are statistically dependent because they share the same, albeit unknown, style. Style constrained classifiers achieve higher classification accuracy by modeling such dependence among patterns in a field. Effects of style consistency on the distributions of field-features (concatenation of pattern features) can be modeled by hierarchical mixtures. Each field derives from a mixture of styles, while, within a field, a pattern derives from a class-style conditional mixture of Gaussians. Based on this model, an optimal style constrained classifier processes entire fields of patterns rendered in a consistent but unknown style. In a laboratory experiment, style constrained classification reduced errors on fields of printed digits by nearly 25 percent over singlet classifiers. Longer fields favor our classification method because they furnish more information about the underlying style.

Toward the characterization of biological toxins using field-based FT-IR spectroscopic instrumentation

NASA Astrophysics Data System (ADS)

Schiering, David W.; Walton, Robert B.; Brown, Christopher W.; Norman, Mark L.; Brewer, Joseph; Scott, James

2004-12-01

IR spectroscopy is a broadly applicable technique for the identification of covalent materials. Recent advances in instrumentation have made Fourier Transform infrared (FT-IR) spectroscopy available for field characterization of suspect materials. Presently, this instrumentation is broadly deployed and used for the identification of potential chemical hazards. This discussion concerns work towards expanding the analytical utility of field-based FT-IR spectrometry in the characterization of biological threats. Two classes of materials were studied: biologically produced chemical toxins which were non-peptide in nature and peptide toxin. The IR spectroscopic identification of aflatoxin-B1, trichothecene T2 mycotoxin, and strychnine was evaluated using the approach of spectral searching against large libraries of materials. For pure components, the IR method discriminated the above toxins at better than the 99% confidence level. The ability to identify non-peptide toxins in mixtures was also evaluated using a "spectral stripping" search approach. For the mixtures evaluated, this method was able to identify the mixture components from ca. 32K spectral library entries. Castor bean extract containing ricin was used as a representative peptide toxin. Due to similarity in protein spectra, a SIMCA pattern recognition methodology was evaluated for classifying peptide toxins. In addition to castor bean extract the method was validated using bovine serum albumin and myoglobin as simulants. The SIMCA approach was successful in correctly classifying these samples at the 95% confidence level.

Charged Particles on Surfaces: Coexistence of Dilute Phases and Periodic Structures at Interfaces

NASA Astrophysics Data System (ADS)

Loverde, Sharon M.; Solis, Francisco J.; Olvera de La Cruz, Monica

2007-06-01

We consider a mixture of two immiscible oppositely charged molecules strongly adsorbed to an interface, with a neutral nonselective molecular background. We determine the coexistence between a high density ionic periodic phase and a dilute isotropic ionic phase. We use a strong segregation approach for the periodic phase and determine the one-loop free energy for the dilute phase. Lamellar and hexagonal patterns are calculated for different charge stoichiometries of the mixture. Molecular dynamics simulations exhibit the predicted phase behavior. The periodic length scale of the solid phase is found to scale as ɛ/(lBψ3/2), where ψ is the effective charge density, lB is the Bjerrum length, and ɛ is the cohesive energy.

Differential gene expression patterns in developing sexually dimorphic rat brain regions exposed to antiandrogenic, estrogenic, or complex endocrine disruptor mixtures: glutamatergic synapses as target.

PubMed

Lichtensteiger, Walter; Bassetti-Gaille, Catherine; Faass, Oliver; Axelstad, Marta; Boberg, Julie; Christiansen, Sofie; Rehrauer, Hubert; Georgijevic, Jelena Kühn; Hass, Ulla; Kortenkamp, Andreas; Schlumpf, Margret

2015-04-01

The study addressed the question whether gene expression patterns induced by different mixtures of endocrine disrupting chemicals (EDCs) administered in a higher dose range, corresponding to 450×, 200×, and 100× high-end human exposure levels, could be characterized in developing brain with respect to endocrine activity of mixture components, and which developmental processes were preferentially targeted. Three EDC mixtures, A-Mix (anti-androgenic mixture) with 8 antiandrogenic chemicals (di-n-butylphthalate, diethylhexylphthalate, vinclozolin, prochloraz, procymidone, linuron, epoxiconazole, and DDE), E-Mix (estrogenic mixture) with 4 estrogenic chemicals (bisphenol A, 4-methylbenzylidene camphor, 2-ethylhexyl 4-methoxycinnamate, and butylparaben), a complex mixture, AEP-Mix, containing the components of A-Mix and E-Mix plus paracetamol, and paracetamol alone, were administered by oral gavage to rat dams from gestation day 7 until weaning. General developmental endpoints were not affected by EDC mixtures or paracetamol. Gene expression was analyzed on postnatal day 6, during sexual brain differentiation, by exon microarray in medial preoptic area in the high-dose group, and by real-time RT-PCR in medial preoptic area and ventromedial hypothalamus in all dose groups. Expression patterns were mixture, sex, and region specific. Effects of the analgesic drug paracetamol, which exhibits antiandrogenic activity in peripheral systems, differed from those of A-Mix. All mixtures had a strong, mixture-specific impact on genes encoding for components of excitatory glutamatergic synapses and genes controlling migration and pathfinding of glutamatergic and GABAergic neurons, as well as genes linked with increased risk of autism spectrum disorders. Because development of glutamatergic synapses is regulated by sex steroids also in hippocampus, this may represent a general target of ECD mixtures.

Mixture risk assessment: a case study of Monsanto experiences.

PubMed

Nair, R S; Dudek, B R; Grothe, D R; Johannsen, F R; Lamb, I C; Martens, M A; Sherman, J H; Stevens, M W

1996-01-01

Monsanto employs several pragmatic approaches for evaluating the toxicity of mixtures. These approaches are similar to those recommended by many national and international agencies. When conducting hazard and risk assessments, priority is always given to using data collected directly on the mixture of concern. To provide an example of the first tier of evaluation, actual data on acute respiratory irritation studies on mixtures were evaluated to determine whether the principle of additivity was applicable to the mixture evaluated. If actual data on the mixture are unavailable, extrapolation across similar mixtures is considered. Because many formulations are quite similar in composition, the toxicity data from one mixture can be extended to a closely related mixture in a scientifically justifiable manner. An example of a family of products where such extrapolations have been made is presented to exemplify this second approach. Lastly, if data on similar mixtures are unavailable, data on component fractions are used to predict the toxicity of the mixture. In this third approach, process knowledge and scientific judgement are used to determine how the known toxicological properties of the individual fractions affect toxicity of the mixture. Three examples of plant effluents where toxicological data on fractions were used to predict the toxicity of the mixture are discussed. The results of the analysis are used to discuss the predictive value of each of the above mentioned toxicological approaches for evaluating chemical mixtures.

Mixture for producing fracture-resistant, fiber-reinforced ceramic material by microwave heating

DOEpatents

Meek, T.T.; Blake, R.D.

1985-04-03

A fracture-resistant, fiber-reinforced ceramic substrate is produced by a method which involves preparing a ceramic precursor mixture comprising glass material, a coupling agent, and resilient fibers, and then exposing the mixture to microwave energy. The microwave field orients the fibers in the resulting ceramic material in a desired pattern wherein heat later generated in or on the substrate can be dissipated in a desired geometric pattern parallel to the fiber pattern. Additionally, the shunt capacitance of the fracture-resistant, fiber-reinforced ceramic substrate is lower which provides for a quicker transit time for electronic pulses in any conducting pathway etched into the ceramic substrate.

Mixture for producing fracture-resistant, fiber-reinforced ceramic material by microwave heating

DOEpatents

Meek, Thomas T.; Blake, Rodger D.

1987-01-01

A fracture-resistant, fiber-reinforced ceramic substrate is produced by a method which involves preparing a ceramic precursor mixture comprising glass material, a coupling agent, and resilient fibers, and then exposing the mixture to microwave energy. The microwave field orients the fibers in the resulting ceramic material in a desired pattern wherein heat later generated in or on the substrate can be dissipated in a desired geometric pattern parallel to the fiber pattern. Additionally, the shunt capacitance of the fracture-resistant, fiber-reinforced ceramic substrate is lower which provides for a quicker transit time for electronic pulses in any conducting pathway etched into the ceramic substrate.

Mixture of autoregressive modeling orders and its implication on single trial EEG classification

PubMed Central

Atyabi, Adham; Shic, Frederick; Naples, Adam

2016-01-01

Autoregressive (AR) models are of commonly utilized feature types in Electroencephalogram (EEG) studies due to offering better resolution, smoother spectra and being applicable to short segments of data. Identifying correct AR’s modeling order is an open challenge. Lower model orders poorly represent the signal while higher orders increase noise. Conventional methods for estimating modeling order includes Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Final Prediction Error (FPE). This article assesses the hypothesis that appropriate mixture of multiple AR orders is likely to better represent the true signal compared to any single order. Better spectral representation of underlying EEG patterns can increase utility of AR features in Brain Computer Interface (BCI) systems by increasing timely & correctly responsiveness of such systems to operator’s thoughts. Two mechanisms of Evolutionary-based fusion and Ensemble-based mixture are utilized for identifying such appropriate mixture of modeling orders. The classification performance of the resultant AR-mixtures are assessed against several conventional methods utilized by the community including 1) A well-known set of commonly used orders suggested by the literature, 2) conventional order estimation approaches (e.g., AIC, BIC and FPE), 3) blind mixture of AR features originated from a range of well-known orders. Five datasets from BCI competition III that contain 2, 3 and 4 motor imagery tasks are considered for the assessment. The results indicate superiority of Ensemble-based modeling order mixture and evolutionary-based order fusion methods within all datasets. PMID:28740331

Modern Methods for Modeling Change in Obesity Research in Nursing.

PubMed

Sereika, Susan M; Zheng, Yaguang; Hu, Lu; Burke, Lora E

2017-08-01

Persons receiving treatment for weight loss often demonstrate heterogeneity in lifestyle behaviors and health outcomes over time. Traditional repeated measures approaches focus on the estimation and testing of an average temporal pattern, ignoring the interindividual variability about the trajectory. An alternate person-centered approach, group-based trajectory modeling, can be used to identify distinct latent classes of individuals following similar trajectories of behavior or outcome change as a function of age or time and can be expanded to include time-invariant and time-dependent covariates and outcomes. Another latent class method, growth mixture modeling, builds on group-based trajectory modeling to investigate heterogeneity within the distinct trajectory classes. In this applied methodologic study, group-based trajectory modeling for analyzing changes in behaviors or outcomes is described and contrasted with growth mixture modeling. An illustration of group-based trajectory modeling is provided using calorie intake data from a single-group, single-center prospective study for weight loss in adults who are either overweight or obese.

Investigating Mixture Interactions of Astringent Stimuli Using the Isobole Approach

PubMed Central

Fleming, Erin E.; Ziegler, Gregory R.

2016-01-01

Abstract Astringents (alum, malic acid, tannic acid) representing 3 broad classes (multivalent salts, organic acids, and polyphenols) were characterized alone, and as 2- and 3-component mixtures using isoboles. In experiment 1, participants rated 7 attributes (“astringency,” the sub-qualities “drying,” “roughing,” and “puckering,” and the side tastes “bitterness,” “sourness,” and “sweetness”) using direct scaling. Quality specific power functions were calculated for each stimulus. In experiment 2, the same participants characterized 2- and 3-component mixtures. Multiple factor analysis (MFA) and hierarchical clustering on attribute ratings across stimuli indicate “astringency” is highly related to “bitterness” as well as “puckering,” and the subqualities “drying” and “roughing” are somewhat redundant. Moreover, power functions were used to calculate indices of interaction (I) for each attribute/mixture combination. For “astringency,” there was evidence of antagonism, regardless of the type of mixture. Conversely, for subqualities, the pattern of interaction depended on the mixture type. Alum/tannic acid and tannic acid/malic acid mixtures showed evidence of synergy for “drying” and “roughing”; alum/malic acid mixtures showed evidence of antagonism for “drying,” “roughing,” and “puckering.” Collectively, these data clarify some semantic ambiguity regarding astringency and its subqualities, as well as the nature of interactions of among different types of astringents. Present data are not inconsistent with the idea that astringency arises from multiple mechanisms, although it remains to be determined whether the synergy observed here might reflect simultaneous activation of these multiple mechanisms. PMID:27252355

An integrated approach using orthogonal analytical techniques to characterize heparan sulfate structure.

PubMed

Beccati, Daniela; Lech, Miroslaw; Ozug, Jennifer; Gunay, Nur Sibel; Wang, Jing; Sun, Elaine Y; Pradines, Joël R; Farutin, Victor; Shriver, Zachary; Kaundinya, Ganesh V; Capila, Ishan

2017-02-01

Heparan sulfate (HS), a glycosaminoglycan present on the surface of cells, has been postulated to have important roles in driving both normal and pathological physiologies. The chemical structure and sulfation pattern (domain structure) of HS is believed to determine its biological function, to vary across tissue types, and to be modified in the context of disease. Characterization of HS requires isolation and purification of cell surface HS as a complex mixture. This process may introduce additional chemical modification of the native residues. In this study, we describe an approach towards thorough characterization of bovine kidney heparan sulfate (BKHS) that utilizes a variety of orthogonal analytical techniques (e.g. NMR, IP-RPHPLC, LC-MS). These techniques are applied to characterize this mixture at various levels including composition, fragment level, and overall chain properties. The combination of these techniques in many instances provides orthogonal views into the fine structure of HS, and in other instances provides overlapping / confirmatory information from different perspectives. Specifically, this approach enables quantitative determination of natural and modified saccharide residues in the HS chains, and identifies unusual structures. Analysis of partially digested HS chains allows for a better understanding of the domain structures within this mixture, and yields specific insights into the non-reducing end and reducing end structures of the chains. This approach outlines a useful framework that can be applied to elucidate HS structure and thereby provides means to advance understanding of its biological role and potential involvement in disease progression. In addition, the techniques described here can be applied to characterization of heparin from different sources.

Rapid Biochemical Mixture Screening by Three-Dimensional Patterned Multifunctional Substrate with Ultra-Thin Layer Chromatography (UTLC) and Surface Enhanced Raman Scattering (SERS).

PubMed

Lee, Bi-Shen; Lin, Pi-Chen; Lin, Ding-Zheng; Yen, Ta-Jen

2018-01-11

We present a three-dimensional patterned (3DP) multifunctional substrate with the functions of ultra-thin layer chromatography (UTLC) and surface enhanced Raman scattering (SERS), which simultaneously enables mixture separation, target localization and label-free detection. This multifunctional substrate is comprised of a 3DP silicon nanowires array (3DP-SiNWA), decorated with silver nano-dendrites (AgNDs) atop. The 3DP-SiNWA is fabricated by a facile photolithographic process and low-cost metal assisted chemical etching (MaCE) process. Then, the AgNDs are decorated onto 3DP-SiNWA by a wet chemical reduction process, obtaining 3DP-AgNDs@SiNWA multifunctional substrates. With various patterns designed on the substrates, the signal intensity could be maximized by the excellent confinement and concentrated effects of patterns. By using this 3DP-AgNDs@SiNWA substrate to scrutinize the mixture of two visible dyes, the individual target could be recognized and further boosted the Raman signal of target 15.42 times comparing to the un-patterned AgNDs@SiNWA substrate. Therefore, such a three-dimensional patterned multifunctional substrate empowers rapid mixture screening, and can be readily employed in practical applications for biochemical assays, food safety and other fields.

Activity of water in aqueous systems; a frequently neglected property.

PubMed

Blandamer, Mike J; Engberts, Jan B F N; Gleeson, Peter T; Reis, Joao Carlos R

2005-05-01

In this critical review, the significance of the term 'activity' is examined in the context of the properties of aqueous solutions. The dependence of the activity of water(l) at ambient pressure and 298.15 K on solute molality is examined for aqueous solutions containing neutral solutes, mixtures of neutral solutes and salts. Addition of a solute to water(l) always lowers its thermodynamic activity. For some solutes the stabilisation of water(l) is less than and for others more than in the case where the thermodynamic properties of the aqueous solution are ideal. In one approach this pattern is accounted for in terms of hydrate formation. Alternatively the pattern is analysed in terms of the dependence of practical osmotic coefficients on the composition of the aqueous solution and then in terms of solute-solute interactions. For salt solutions the dependence of the activity of water on salt molalities is compared with that predicted by the Debye-Hückel limiting law. The analysis is extended to consideration of the activities of water in binary aqueous mixtures. The dependence on mole fraction composition of the activity of water in binary aqueous mixtures is examined. Different experimental methods for determining the activity of water in aqueous solutions are critically reviewed. The role of water activity is noted in a biochemical context, with reference to the quality, stability and safety of food and finally with regard to health science.

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

PubMed

Tang, Yongqiang

2018-04-30

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods. Copyright © 2018 John Wiley & Sons, Ltd.

Mixture for producing fracture-resistant, fiber-reinforced ceramic material by microwave heating

DOEpatents

Meek, T.T.; Blake, R.D.

1987-09-22

A fracture-resistant, fiber-reinforced ceramic substrate is produced by a method which involves preparing a ceramic precursor mixture comprising glass material, a coupling agent, and resilient fibers, and then exposing the mixture to microwave energy. The microwave field orients the fibers in the resulting ceramic material in a desired pattern wherein heat later generated in or on the substrate can be dissipated in a desired geometric pattern parallel to the fiber pattern. Additionally, the shunt capacitance of the fracture-resistant, fiber-reinforced ceramic substrate is lower which provides for a quicker transit time for electronic pulses in any conducting pathway etched into the ceramic substrate. 2 figs.

Rapid Copper Metallization of Textile Materials: a Controlled Two-Step Route to Achieve User-Defined Patterns under Ambient Conditions.

PubMed

Zhang, Shuang-Yuan; Guan, Guijian; Jiang, Shan; Guo, Hongchen; Xia, Jing; Regulacio, Michelle D; Wu, Mingda; Shah, Kwok Wei; Dong, Zhili; Zhang, Jie; Han, Ming-Yong

2015-09-30

Throughout history earth-abundant copper has been incorporated into textiles and it still caters to various needs in modern society. In this paper, we present a two-step copper metallization strategy to realize sequentially nondiffusive copper(II) patterning and rapid copper deposition on various textile materials, including cotton, polyester, nylon, and their mixtures. A new, cost-effective formulation is designed to minimize the copper pattern migration on textiles and to achieve user-defined copper patterns. The metallized copper is found to be very adhesive and stable against washing and oxidation. Furthermore, the copper-metallized textile exhibits excellent electrical conductivity that is ~3 times better than that of stainless steel and also inhibits the growth of bacteria effectively. This new copper metallization approach holds great promise as a commercially viable method to metallize an insulating textile, opening up research avenues for wearable electronics and functional garments.

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices.

PubMed

Bellier, Edwige; Grøtan, Vidar; Engen, Steinar; Schartau, Ann Kristin; Diserud, Ola H; Finstad, Anders G

2012-10-01

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.

Patterning ecological risk of pesticide contamination at the river basin scale.

PubMed

Faggiano, Leslie; de Zwart, Dick; García-Berthou, Emili; Lek, Sovan; Gevrey, Muriel

2010-05-01

Ecological risk assessment was conducted to determine the risk posed by pesticide mixtures to the Adour-Garonne river basin (south-western France). The objectives of this study were to assess the general state of this basin with regard to pesticide contamination using a risk assessment procedure and to detect patterns in toxic mixture assemblages through a self-organizing map (SOM) methodology in order to identify the locations at risk. Exposure assessment, risk assessment with species sensitivity distribution, and mixture toxicity rules were used to compute six relative risk predictors for different toxic modes of action: the multi-substance potentially affected fraction of species depending on the toxic mode of action of compounds found in the mixture (msPAF CA(TMoA) values). Those predictors computed for the 131 sampling sites assessed in this study were then patterned through the SOM learning process. Four clusters of sampling sites exhibiting similar toxic assemblages were identified. In the first cluster, which comprised 83% of the sampling sites, the risk caused by pesticide mixture toward aquatic species was weak (mean msPAF value for those sites<0.0036%), while in another cluster the risk was significant (mean msPAF<1.09%). GIS mapping allowed an interesting spatial pattern of the distribution of sampling sites for each cluster to be highlighted with a significant and highly localized risk in the French department called "Lot et Garonne". The combined use of the SOM methodology, mixture toxicity modelling and a clear geo-referenced representation of results not only revealed the general state of the Adour-Garonne basin with regard to contamination by pesticides but also enabled to analyze the spatial pattern of toxic mixture assemblage in order to prioritize the locations at risk and to detect the group of compounds causing the greatest risk at the basin scale. Copyright 2010 Elsevier B.V. All rights reserved.

Definition of natural T cell antigens with mimicry epitopes obtained from dedicated synthetic peptide libraries.

PubMed

Hiemstra, H S; van Veelen, P A; Schloot, N C; Geluk, A; van Meijgaarden, K E; Willemen, S J; Leunissen, J A; Benckhuijsen, W E; Amons, R; de Vries, R R; Roep, B O; Ottenhoff, T H; Drijfhout, J W

1998-10-15

Progress has recently been made in the use of synthetic peptide libraries for the identification of T cell-stimulating ligands. T cell epitopes identified from synthetic libraries are mimics of natural epitopes. Here we show how the mimicry epitopes obtained from synthetic peptide libraries enable unambiguous identification of natural T cell Ags. Synthetic peptide libraries were screened with Mycobacterium tuberculosis-reactive and -autoreactive T cell clones. In two cases, database homology searches with mimicry epitopes isolated from a dedicated synthetic peptide library allowed immediate identification of the natural antigenic protein. In two other cases, an amino acid pattern that reflected the epitope requirements of the T cell was determined by substitution and omission mixture analysis. Subsequently, the natural Ag was identified from databases using this refined pattern. This approach opens new perspectives for rapid and reliable Ag definition, representing a feasible alternative to the biochemical and genetic approaches described thus far.

Mixture experiment methods in the development and optimization of microemulsion formulations

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

Furlanetto, Sandra; Cirri, Marzia; Piepel, Gregory F.

2011-06-25

Microemulsion formulations represent an interesting delivery vehicle for lipophilic drugs, allowing for improving their solubility and dissolution properties. This work developed effective microemulsion formulations using glyburide (a very poorly-water-soluble hypoglycaemic agent) as a model drug. First, the area of stable microemulsion (ME) formations was identified using a new approach based on mixture experiment methods. A 13-run mixture design was carried out in an experimental region defined by constraints on three components: aqueous, oil, and surfactant/cosurfactant. The transmittance percentage (at 550 nm) of ME formulations (indicative of their transparency and thus of their stability) was chosen as the response variable. Themore » results obtained using the mixture experiment approach corresponded well with those obtained using the traditional approach based on pseudo-ternary phase diagrams. However, the mixture experiment approach required far less experimental effort than the traditional approach. A subsequent 13-run mixture experiment, in the region of stable MEs, was then performed to identify the optimal formulation (i.e., having the best glyburide dissolution properties). Percent drug dissolved and dissolution efficiency were selected as the responses to be maximized. The ME formulation optimized via the mixture experiment approach consisted of 78% surfactant/cosurfacant (a mixture of Tween 20 and Transcutol, 1:1 v/v), 5% oil (Labrafac Hydro) and 17% aqueous (water). The stable region of MEs was identified using mixture experiment methods for the first time.« less

Testing treatment effect in schizophrenia clinical trials with heavy patient dropout using latent class growth mixture models.

PubMed

Kong, Fanhui; Chen, Yeh-Fong

2016-07-01

By examining the outcome trajectories of the dropout patients with different reasons in the schizophrenia trials, we note that although patients are recruited from the same protocol that have compatible baseline characteristics, they may respond differently even to the same treatment. Some patients show consistent improvement while others only have temporary relief. This creates different patient subpopulations characterized by their response and dropout patterns. At the same time, those who continue to improve seem to be more likely to complete the study while those who only experience temporary relief have a higher chance to drop out. Such phenomenon appears to be quite general in schizophrenia clinical trials. This simultaneous inhomogeneity both in patient response as well as dropout patterns creates a scenario of missing not at random and therefore results in biases when we use the statistical methods based on the missing at random assumption to test treatment efficacy. In this paper, we propose to use the latent class growth mixture model, which is a special case of the latent mixture model, to conduct the statistical analyses in such situation. This model allows us to take the inhomogeneity among subpopulations into consideration to make more accurate inferences on the treatment effect at any visit time. Comparing with the conventional statistical methods such as mixed-effects model for repeated measures, we demonstrate through simulations that the proposed latent mixture model approach gives better control on the Type I error rate in testing treatment effect. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. Copyright © 2016 John Wiley & Sons, Ltd.

A Fourier approach to cloud motion estimation

NASA Technical Reports Server (NTRS)

Arking, A.; Lo, R. C.; Rosenfield, A.

1977-01-01

A Fourier technique is described for estimating cloud motion from pairs of pictures using the phase of the cross spectral density. The method allows motion estimates to be made for individual spatial frequencies, which are related to cloud pattern dimensions. Results obtained are presented and compared with the results of a Fourier domain cross correlation scheme. Using both artificial and real cloud data show that the technique is relatively sensitive to the presence of mixtures of motions, changes in cloud shape, and edge effects.

A Novel Approach for Evaluating Carbamate Mixtures for Dose Additivity

EPA Science Inventory

Two mathematical approaches were used to test the hypothesis ofdose-addition for a binary and a seven-chemical mixture ofN-methyl carbamates, toxicologically similar chemicals that inhibit cholinesterase (ChE). In the more novel approach, mixture data were not included in the ana...

An integrative approach to assess X-chromosome inactivation using allele-specific expression with applications to epithelial ovarian cancer.

PubMed

Larson, Nicholas B; Fogarty, Zachary C; Larson, Melissa C; Kalli, Kimberly R; Lawrenson, Kate; Gayther, Simon; Fridley, Brooke L; Goode, Ellen L; Winham, Stacey J

2017-12-01

X-chromosome inactivation (XCI) epigenetically silences transcription of an X chromosome in females; patterns of XCI are thought to be aberrant in women's cancers, but are understudied due to statistical challenges. We develop a two-stage statistical framework to assess skewed XCI and evaluate gene-level patterns of XCI for an individual sample by integration of RNA sequence, copy number alteration, and genotype data. Our method relies on allele-specific expression (ASE) to directly measure XCI and does not rely on male samples or paired normal tissue for comparison. We model ASE using a two-component mixture of beta distributions, allowing estimation for a given sample of the degree of skewness (based on a composite likelihood ratio test) and the posterior probability that a given gene escapes XCI (using a Bayesian beta-binomial mixture model). To illustrate the utility of our approach, we applied these methods to data from tumors of ovarian cancer patients. Among 99 patients, 45 tumors were informative for analysis and showed evidence of XCI skewed toward a particular parental chromosome. For 397 X-linked genes, we observed tumor XCI patterns largely consistent with previously identified consensus states based on multiple normal tissue types. However, 37 genes differed in XCI state between ovarian tumors and the consensus state; 17 genes aberrantly escaped XCI in ovarian tumors (including many oncogenes), whereas 20 genes were unexpectedly inactivated in ovarian tumors (including many tumor suppressor genes). These results provide evidence of the importance of XCI in ovarian cancer and demonstrate the utility of our two-stage analysis. © 2017 WILEY PERIODICALS, INC.

A Four Step Approach to Evaluate Mixtures for Consistency with Dose Addition

EPA Science Inventory

We developed a four step approach for evaluating chemical mixture data for consistency with dose addition for use in environmental health risk assessment. Following the concepts in the U.S. EPA mixture risk guidance (EPA 2000a,b), toxicological interaction for a defined mixture (...

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.

Mixture experiment methods in the development and optimization of microemulsion formulations.

PubMed

Furlanetto, S; Cirri, M; Piepel, G; Mennini, N; Mura, P

2011-06-25

Microemulsion formulations represent an interesting delivery vehicle for lipophilic drugs, allowing for improving their solubility and dissolution properties. This work developed effective microemulsion formulations using glyburide (a very poorly-water-soluble hypoglycaemic agent) as a model drug. First, the area of stable microemulsion (ME) formations was identified using a new approach based on mixture experiment methods. A 13-run mixture design was carried out in an experimental region defined by constraints on three components: aqueous, oil and surfactant/cosurfactant. The transmittance percentage (at 550 nm) of ME formulations (indicative of their transparency and thus of their stability) was chosen as the response variable. The results obtained using the mixture experiment approach corresponded well with those obtained using the traditional approach based on pseudo-ternary phase diagrams. However, the mixture experiment approach required far less experimental effort than the traditional approach. A subsequent 13-run mixture experiment, in the region of stable MEs, was then performed to identify the optimal formulation (i.e., having the best glyburide dissolution properties). Percent drug dissolved and dissolution efficiency were selected as the responses to be maximized. The ME formulation optimized via the mixture experiment approach consisted of 78% surfactant/cosurfacant (a mixture of Tween 20 and Transcutol, 1:1, v/v), 5% oil (Labrafac Hydro) and 17% aqueous phase (water). The stable region of MEs was identified using mixture experiment methods for the first time. Copyright © 2011 Elsevier B.V. All rights reserved.

NEUROTOXICOLOGICAL AND STATISTICAL ANALYSES OF A MIXTURE OF FIVE ORGANOPHOSPHORUS PESTICIDES USING A RAY DESIGN.

EPA Science Inventory

Pesticide application patterns generally result in exposure to mixtures instead of single chemicals. Of particular importance in the estimation of pesticide mixture risks is the detection and characterization of their interactions. This research tested for interaction(s) in a mix...

A multimodal imaging workflow to visualize metal mixtures in the human placenta and explore colocalization with biological response markers.

PubMed

Niedzwiecki, Megan M; Austin, Christine; Remark, Romain; Merad, Miriam; Gnjatic, Sacha; Estrada-Gutierrez, Guadalupe; Espejel-Nuñez, Aurora; Borboa-Olivares, Hector; Guzman-Huerta, Mario; Wright, Rosalind J; Wright, Robert O; Arora, Manish

2016-04-01

Fetal exposure to essential and toxic metals can influence life-long health trajectories. The placenta regulates chemical transmission from maternal circulation to the fetus and itself exhibits a complex response to environmental stressors. The placenta can thus be a useful matrix to monitor metal exposures and stress responses in utero, but strategies to explore the biologic effects of metal mixtures in this organ are not well-developed. In this proof-of-concept study, we used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to measure the distributions of multiple metals in placental tissue from a low-birth-weight pregnancy, and we developed an approach to identify the components of metal mixtures that colocalized with biological response markers. Our novel workflow, which includes custom-developed software tools and algorithms for spatial outlier identification and background subtraction in multidimensional elemental image stacks, enables rapid image processing and seamless integration of data from elemental imaging and immunohistochemistry. Using quantitative spatial statistics, we identified distinct patterns of metal accumulation at sites of inflammation. Broadly, our multiplexed approach can be used to explore the mechanisms mediating complex metal exposures and biologic responses within placentae and other tissue types. Our LA-ICP-MS image processing workflow can be accessed through our interactive R Shiny application 'shinyImaging', which is available at or through our laboratory's website, .

Clustered mixed nonhomogeneous Poisson process spline models for the analysis of recurrent event panel data.

PubMed

Nielsen, J D; Dean, C B

2008-09-01

A flexible semiparametric model for analyzing longitudinal panel count data arising from mixtures is presented. Panel count data refers here to count data on recurrent events collected as the number of events that have occurred within specific follow-up periods. The model assumes that the counts for each subject are generated by mixtures of nonhomogeneous Poisson processes with smooth intensity functions modeled with penalized splines. Time-dependent covariate effects are also incorporated into the process intensity using splines. Discrete mixtures of these nonhomogeneous Poisson process spline models extract functional information from underlying clusters representing hidden subpopulations. The motivating application is an experiment to test the effectiveness of pheromones in disrupting the mating pattern of the cherry bark tortrix moth. Mature moths arise from hidden, but distinct, subpopulations and monitoring the subpopulation responses was of interest. Within-cluster random effects are used to account for correlation structures and heterogeneity common to this type of data. An estimating equation approach to inference requiring only low moment assumptions is developed and the finite sample properties of the proposed estimating functions are investigated empirically by simulation.

Partitioning into hazard subregions for regional peaks-over-threshold modeling of heavy precipitation

NASA Astrophysics Data System (ADS)

Carreau, J.; Naveau, P.; Neppel, L.

2017-05-01

The French Mediterranean is subject to intense precipitation events occurring mostly in autumn. These can potentially cause flash floods, the main natural danger in the area. The distribution of these events follows specific spatial patterns, i.e., some sites are more likely to be affected than others. The peaks-over-threshold approach consists in modeling extremes, such as heavy precipitation, by the generalized Pareto (GP) distribution. The shape parameter of the GP controls the probability of extreme events and can be related to the hazard level of a given site. When interpolating across a region, the shape parameter should reproduce the observed spatial patterns of the probability of heavy precipitation. However, the shape parameter estimators have high uncertainty which might hide the underlying spatial variability. As a compromise, we choose to let the shape parameter vary in a moderate fashion. More precisely, we assume that the region of interest can be partitioned into subregions with constant hazard level. We formalize the model as a conditional mixture of GP distributions. We develop a two-step inference strategy based on probability weighted moments and put forward a cross-validation procedure to select the number of subregions. A synthetic data study reveals that the inference strategy is consistent and not very sensitive to the selected number of subregions. An application on daily precipitation data from the French Mediterranean shows that the conditional mixture of GPs outperforms two interpolation approaches (with constant or smoothly varying shape parameter).

Mining patterns in persistent surveillance systems with smart query and visual analytics

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.; Shirkhodaie, Amir

2013-05-01

In Persistent Surveillance Systems (PSS) the ability to detect and characterize events geospatially help take pre-emptive steps to counter adversary's actions. Interactive Visual Analytic (VA) model offers this platform for pattern investigation and reasoning to comprehend and/or predict such occurrences. The need for identifying and offsetting these threats requires collecting information from diverse sources, which brings with it increasingly abstract data. These abstract semantic data have a degree of inherent uncertainty and imprecision, and require a method for their filtration before being processed further. In this paper, we have introduced an approach based on Vector Space Modeling (VSM) technique for classification of spatiotemporal sequential patterns of group activities. The feature vectors consist of an array of attributes extracted from generated sensors semantic annotated messages. To facilitate proper similarity matching and detection of time-varying spatiotemporal patterns, a Temporal-Dynamic Time Warping (DTW) method with Gaussian Mixture Model (GMM) for Expectation Maximization (EM) is introduced. DTW is intended for detection of event patterns from neighborhood-proximity semantic frames derived from established ontology. GMM with EM, on the other hand, is employed as a Bayesian probabilistic model to estimated probability of events associated with a detected spatiotemporal pattern. In this paper, we present a new visual analytic tool for testing and evaluation group activities detected under this control scheme. Experimental results demonstrate the effectiveness of proposed approach for discovery and matching of subsequences within sequentially generated patterns space of our experiments.

Evaluating the Similarity of Complex Drinking-Water Disinfection By-Product Mixtures: Overview of the Issues

EPA Science Inventory

The Presentation describes the advantages and challenges of working with Whole Mixtures, discusses an exploratory approach for evaluating sufficient similarity, and challenges of applying such approaches to other environmental mixtures.

Computational Fluid Dynamics modeling of contrast transport in basilar aneurysms following flow-altering surgeries.

PubMed

Vali, Alireza; Abla, Adib A; Lawton, Michael T; Saloner, David; Rayz, Vitaliy L

2017-01-04

In vivo measurement of blood velocity fields and flow descriptors remains challenging due to image artifacts and limited resolution of current imaging methods; however, in vivo imaging data can be used to inform and validate patient-specific computational fluid dynamics (CFD) models. Image-based CFD can be particularly useful for planning surgical interventions in complicated cases such as fusiform aneurysms of the basilar artery, where it is crucial to alter pathological hemodynamics while preserving flow to the distal vasculature. In this study, patient-specific CFD modeling was conducted for two basilar aneurysm patients considered for surgical treatment. In addition to velocity fields, transport of contrast agent was simulated for the preoperative and postoperative conditions using two approaches. The transport of a virtual contrast passively following the flow streamlines was simulated to predict post-surgical flow regions prone to thrombus deposition. In addition, the transport of a mixture of blood with an iodine-based contrast agent was modeled to compare and verify the CFD results with X-ray angiograms. The CFD-predicted patterns of contrast flow were qualitatively compared to in vivo X-ray angiograms acquired before and after the intervention. The results suggest that the mixture modeling approach, accounting for the flow rates and properties of the contrast injection, is in better agreement with the X-ray angiography data. The virtual contrast modeling assessed the residence time based on flow patterns unaffected by the injection procedure, which makes the virtual contrast modeling approach better suited for prediction of thrombus deposition, which is not limited to the peri-procedural state. Copyright © 2016 Elsevier Ltd. All rights reserved.

Additivity and Interactions in Ecotoxicity of Pollutant Mixtures: Some Patterns, Conclusions, and Open Questions

PubMed Central

Rodea-Palomares, Ismael; González-Pleiter, Miguel; Martín-Betancor, Keila; Rosal, Roberto; Fernández-Piñas, Francisca

2015-01-01

Understanding the effects of exposure to chemical mixtures is a common goal of pharmacology and ecotoxicology. In risk assessment-oriented ecotoxicology, defining the scope of application of additivity models has received utmost attention in the last 20 years, since they potentially allow one to predict the effect of any chemical mixture relying on individual chemical information only. The gold standard for additivity in ecotoxicology has demonstrated to be Loewe additivity which originated the so-called Concentration Addition (CA) additivity model. In pharmacology, the search for interactions or deviations from additivity (synergism and antagonism) has similarly captured the attention of researchers over the last 20 years and has resulted in the definition and application of the Combination Index (CI) Theorem. CI is based on Loewe additivity, but focused on the identification and quantification of synergism and antagonism. Despite additive models demonstrating a surprisingly good predictive power in chemical mixture risk assessment, concerns still exist due to the occurrence of unpredictable synergism or antagonism in certain experimental situations. In the present work, we summarize the parallel history of development of CA, IA, and CI models. We also summarize the applicability of these concepts in ecotoxicology and how their information may be integrated, as well as the possibility of prediction of synergism. Inside the box, the main question remaining is whether it is worthy to consider departures from additivity in mixture risk assessment and how to predict interactions among certain mixture components. Outside the box, the main question is whether the results observed under the experimental constraints imposed by fractional approaches are a de fide reflection of what it would be expected from chemical mixtures in real world circumstances. PMID:29051468

How good is the turbid medium-based approach for accounting for light partitioning in contrasted grass--legume intercropping systems?

PubMed

Barillot, Romain; Louarn, Gaëtan; Escobar-Gutiérrez, Abraham J; Huynh, Pierre; Combes, Didier

2011-10-01

Most studies dealing with light partitioning in intercropping systems have used statistical models based on the turbid medium approach, thus assuming homogeneous canopies. However, these models could not be directly validated although spatial heterogeneities could arise in such canopies. The aim of the present study was to assess the ability of the turbid medium approach to accurately estimate light partitioning within grass-legume mixed canopies. Three contrasted mixtures of wheat-pea, tall fescue-alfalfa and tall fescue-clover were sown according to various patterns and densities. Three-dimensional plant mock-ups were derived from magnetic digitizations carried out at different stages of development. The benchmarks for light interception efficiency (LIE) estimates were provided by the combination of a light projective model and plant mock-ups, which also provided the inputs of a turbid medium model (SIRASCA), i.e. leaf area index and inclination. SIRASCA was set to gradually account for vertical heterogeneity of the foliage, i.e. the canopy was described as one, two or ten horizontal layers of leaves. Mixtures exhibited various and heterogeneous profiles of foliar distribution, leaf inclination and component species height. Nevertheless, most of the LIE was satisfactorily predicted by SIRASCA. Biased estimations were, however, observed for (1) grass species and (2) tall fescue-alfalfa mixtures grown at high density. Most of the discrepancies were due to vertical heterogeneities and were corrected by increasing the vertical description of canopies although, in practice, this would require time-consuming measurements. The turbid medium analogy could be successfully used in a wide range of canopies. However, a more detailed description of the canopy is required for mixtures exhibiting vertical stratifications and inter-/intra-species foliage overlapping. Architectural models remain a relevant tool for studying light partitioning in intercropping systems that exhibit strong vertical heterogeneities. Moreover, these models offer the possibility to integrate the effects of microclimate variations on plant growth.

Canopy and leaf composition drive patterns of nutrient release from pruning residues in a coffee agroforest.

PubMed

Tully, Katherine L; Lawrence, Deborah

2012-06-01

In a coffee agroforest, the crop is cultivated under the shade of fruit-bearing and nitrogen (N)-fixing trees. These trees are periodically pruned to promote flowering and fruiting as well as to make nutrients stored in tree biomass available to plants. We investigated the effect of canopy composition and substrate quality on decomposition rates and patterns of nutrient release from pruning residues in a coffee agroforest located in Costa Rica's Central Valley. Initial phosphorus (P) release was enhanced under a canopy composed solely of N-fixing, Erythrina poeppigiana compared to a mixed canopy of Erythrina and Musa acuminata (banana). Both initial and final N release were similar under the two canopy types. However, after five months of decomposition, a higher proportion of initial N had been released under the single canopy. Although patterns of decomposition and nutrient release were not predicted by initial substrate quality, mass loss in leaf mixtures rates were well predicted by mean mass loss of their component species. This study identifies specific pruning regimes that may regulate N and P release during crucial growth periods, and it suggests that strategic pruning can enhance nutrient availability. For example, during the onset of rapid fruit growth, a two-species mixture may release more P than a three-species mixture. However, by the time of the harvest, the two- and three-species mixtures have released roughly the same amount of N and P. These nutrients do not always follow the same pattern, as N release can be maximized in single-species substrates, while P release is often facilitated in species mixtures. Our study indicates the importance of management practices in mediating patterns of nutrient release. Future research should investigate how canopy composition and farm management can also mediate on-farm nutrient losses.

Exploring the Roles of Extracurricular Activity Quantity and Quality in the Educational Resilience of Vulnerable Adolescents: Variable- and Pattern-Centered Approaches

PubMed Central

Peck, Stephen C.; Roeser, Robert W.; Zarrett, Nicole; Eccles, Jacquelynne S.

2009-01-01

This longitudinal study examines how extracurricular activity involvement contributes to “educational resilience”—the unexpected educational attainments of adolescents who are otherwise vulnerable to curtailed school success due to personal- and social-level risks. Educationally vulnerable youth characterized by significant risks and an absence of assets were identified during early adolescence (approximately age 14) using measures of academic motivation, achievement, and mental health as well as family, school, and peer contexts. Using a mixture of variable- and pattern-centered analytic techniques, we investigate how both the total amount time that vulnerable youth spent in positive extracurricular activities and the specific pattern of their extracurricular activity involvement during late adolescence (approximately age 17) predict their subsequent enrollment in college during early adulthood (up through approximately age 21). Educational resilience was predicted uniquely by some, but not all, activity patterns. These results suggest that positive extracurricular activity settings afford vulnerable youth developmentally appropriate experiences that promote educational persistence and healthy development. PMID:19543445

Exploring the Roles of Extracurricular Activity Quantity and Quality in the Educational Resilience of Vulnerable Adolescents: Variable- and Pattern-Centered Approaches.

PubMed

Peck, Stephen C; Roeser, Robert W; Zarrett, Nicole; Eccles, Jacquelynne S

2008-01-01

This longitudinal study examines how extracurricular activity involvement contributes to "educational resilience"-the unexpected educational attainments of adolescents who are otherwise vulnerable to curtailed school success due to personal- and social-level risks. Educationally vulnerable youth characterized by significant risks and an absence of assets were identified during early adolescence (approximately age 14) using measures of academic motivation, achievement, and mental health as well as family, school, and peer contexts. Using a mixture of variable- and pattern-centered analytic techniques, we investigate how both the total amount time that vulnerable youth spent in positive extracurricular activities and the specific pattern of their extracurricular activity involvement during late adolescence (approximately age 17) predict their subsequent enrollment in college during early adulthood (up through approximately age 21). Educational resilience was predicted uniquely by some, but not all, activity patterns. These results suggest that positive extracurricular activity settings afford vulnerable youth developmentally appropriate experiences that promote educational persistence and healthy development.

User Guide to RockJock - A Program for Determining Quantitative Mineralogy from X-Ray Diffraction Data

USGS Publications Warehouse

Eberl, D.D.

2003-01-01

RockJock is a computer program that determines quantitative mineralogy in powdered samples by comparing the integrated X-ray diffraction (XRD) intensities of individual minerals in complex mixtures to the intensities of an internal standard. Analysis without an internal standard (standardless analysis) also is an option. This manual discusses how to prepare and X-ray samples and mineral standards for these types of analyses and describes the operation of the program. Carefully weighed samples containing an internal standard (zincite) are ground in a McCrone mill. Randomly oriented preparations then are X-rayed, and the X-ray data are entered into the RockJock program. Minerals likely to be present in the sample are chosen from a list of standards, and the calculation is begun. The program then automatically fits the sum of stored XRD patterns of pure standard minerals (the calculated pattern) to the measured pattern by varying the fraction of each mineral standard pattern, using the Solver function in Microsoft Excel to minimize a degree of fit parameter between the calculated and measured pattern. The calculation analyzes the pattern (usually 20 to 65 degrees two-theta) to find integrated intensities for the minerals. Integrated intensities for each mineral then are determined from the proportion of each mineral standard pattern required to give the best fit. These integrated intensities then are compared to the integrated intensity of the internal standard, and the weight percentages of the minerals are calculated. The results are presented as a list of minerals with their corresponding weight percent. To some extent, the quality of the analysis can be checked because each mineral is analyzed independently, and, therefore, the sum of the analysis should approach 100 percent. Also, the method has been shown to give good results with artificial mixtures. The program is easy to use, but does require an understanding of mineralogy, of X-ray diffraction practice, and an elementary knowledge of the Excel program.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Internal flow patterns on heat transfer characteristics of a closed-loop oscillating heat-pipe with check valves using ethanol and a silver nano-ethanol mixture

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

Bhuwakietkumjohn, N.; Rittidech, S.

The aim of this research was to investigate the internal flow patterns and heat transfer characteristics of a closed-loop oscillating heat-pipe with check valves (CLOHP/CV). The ratio of number of check valves to meandering turns was 0.2. Ethanol and a silver nano-ethanol mixture were used as working fluids with a filling ratio of 50% by total volume of tube. The CLOHP/CV was made of a glass tube with an inside diameter of 2.4 mm. The evaporator section was 50 mm and 100 mm in length and there were 10 meandering turns. An inclination angle of 90 from horizontal axis wasmore » established. The evaporator section was heated by an electric heater and the condenser section was cooled by distilled water. Temperature at the evaporator section was controlled at 85 C, 105 C and 125 C. The inlet and outlet temperatures were measured. A digital camera and video camera were used to observe the flow patterns at the evaporator. The silver nano-ethanol mixture gave higher heat flux than ethanol. When the temperature at the evaporator section was increased from 85 C to 105 C and 125 C. It was found that, the flow patterns occurred as annular flow + slug flow, slug flow + bubble flow and dispersed bubble flow + bubble flow respectively. The main regime of each flow pattern can be determined from the flow pattern map ethanol and a silver nano-ethanol mixture. Each of the two working fluids gave corresponding flow patterns. (author)« less

Capturing Parenting as a Multidimensional and Dynamic Construct with a Person-Oriented Approach.

PubMed

Zheng, Yao; Pasalich, Dave S; Oberth, Carla; McMahon, Robert J; Pinderhughes, Ellen E

2017-04-01

Although parenting is one of the most commonly studied predictors of child problem behavior, few studies have examined parenting as a multidimensional and dynamic construct. This study investigated different patterns of developmental trajectories of two parenting dimensions (harsh discipline [HD] and parental warmth [PW]) with a person-oriented approach and examined the associations between different parenting patterns and child externalizing problems and callous-unemotional traits. Data were drawn from the combined high-risk control and normative sample (n = 753) of the Fast Track Project. Parent-reported HD and observer-reported PW from kindergarten to grade 2 were fit to growth mixture models. Two subgroups were identified for HD (low decreasing, 83.0 %; high stable, 17.0 %) and PW (high increasing, 78.7 %; low increasing, 21.3 %). The majority of parents (67.0 %) demonstrated the low decreasing HD and high increasing PW pattern, while the prevalence of the high stable HD and low increasing PW pattern was the lowest (6.8 %). Parenting satisfaction, parental depression, family socioeconomic status, and neighborhood safety predicted group memberships jointly defined by the two dimensions. Children from the high stable HD and low increasing PW pattern showed the highest levels of externalizing problems in grades 4 and 5. Children from the low decreasing HD and low increasing PW pattern showed the highest levels of callous-unemotional traits in grade 7. These findings demonstrate the utility and significance of a person-oriented approach to measuring parenting as a multidimensional and dynamic construct and reveal the interplay between HD and PW in terms of their influences on child developmental outcomes.

Selective Sensing of Gas Mixture via a Temperature Modulation Approach: New Strategy for Potentiometric Gas Sensor Obtaining Satisfactory Discriminating Features.

PubMed

Li, Fu-An; Jin, Han; Wang, Jinxia; Zou, Jie; Jian, Jiawen

2017-03-12

A new strategy to discriminate four types of hazardous gases is proposed in this research. Through modulating the operating temperature and the processing response signal with a pattern recognition algorithm, a gas sensor consisting of a single sensing electrode, i.e., ZnO/In₂O₃ composite, is designed to differentiate NO₂, NH₃, C₃H₆, CO within the level of 50-400 ppm. Results indicate that with adding 15 wt.% ZnO to In₂O₃, the sensor fabricated at 900 °C shows optimal sensing characteristics in detecting all the studied gases. Moreover, with the aid of the principle component analysis (PCA) algorithm, the sensor operating in the temperature modulation mode demonstrates acceptable discrimination features. The satisfactory discrimination features disclose the future that it is possible to differentiate gas mixture efficiently through operating a single electrode sensor at temperature modulation mode.

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.

Mixture IRT Model with a Higher-Order Structure for Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu

2017-01-01

Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…

A Four-step Approach for Evaluation of Dose Additivity

EPA Science Inventory

A four step approach was developed for evaluating toxicity data on a chemical mixture for consistency with dose addition. Following the concepts in the U.S. EPA mixture guidance (EPA 2000), toxicologic interaction for a defined mixture (all components known) is departure from a c...

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

A Four-Step and Four-Criteria Approach for Evaluating Evidence of Dose Addition in Chemical Mixture Toxicity

EPA Science Inventory

Dose addition is the most frequently-used component-based approach for predicting dose response for a mixture of toxicologically-similar chemicals and for statistical evaluation of whether the mixture response is consistent with dose additivity and therefore predictable from the ...

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…

Gradient polymer network liquid crystal with a large refractive index change.

PubMed

Ren, Hongwen; Xu, Su; Wu, Shin-Tson

2012-11-19

A simple approach for preparing gradient polymer network liquid crystal (PNLC) with a large refractive index change is demonstrated. To control the effective refractive index at a given cell position, we applied a voltage to a homogeneous cell containing LC/diacrylate monomer mixture to generate the desired tilt angle and then stabilize the LC orientation with UV-induced polymer network. By varying the applied voltage along with the cells' movement, a PNLC with a gradient refractive index distribution is obtained. In comparison with conventional approaches using patterned photomask or electrode, our method offers following advantages: large refractive index change, freedom to design specific index profile, and large panel capability. Potential applications include tunable-focus lenses, prism gratings, phase modulators, and other adaptive photonic devices.

Prospective mixture risk assessment and management prioritizations for river catchments with diverse land uses

PubMed Central

Brown, Colin D.; de Zwart, Dick; Diamond, Jerome; Dyer, Scott D.; Holmes, Christopher M.; Marshall, Stuart; Burton, G. Allen

2018-01-01

Abstract Ecological risk assessment increasingly focuses on risks from chemical mixtures and multiple stressors because ecosystems are commonly exposed to a plethora of contaminants and nonchemical stressors. To simplify the task of assessing potential mixture effects, we explored 3 land use–related chemical emission scenarios. We applied a tiered methodology to judge the implications of the emissions of chemicals from agricultural practices, domestic discharges, and urban runoff in a quantitative model. The results showed land use–dependent mixture exposures, clearly discriminating downstream effects of land uses, with unique chemical “signatures” regarding composition, concentration, and temporal patterns. Associated risks were characterized in relation to the land‐use scenarios. Comparisons to measured environmental concentrations and predicted impacts showed relatively good similarity. The results suggest that the land uses imply exceedances of regulatory protective environmental quality standards, varying over time in relation to rain events and associated flow and dilution variation. Higher‐tier analyses using ecotoxicological effect criteria confirmed that species assemblages may be affected by exposures exceeding no‐effect levels and that mixture exposure could be associated with predicted species loss under certain situations. The model outcomes can inform various types of prioritization to support risk management, including a ranking across land uses as a whole, a ranking on characteristics of exposure times and frequencies, and various rankings of the relative role of individual chemicals. Though all results are based on in silico assessments, the prospective land use–based approach applied in the present study yields useful insights for simplifying and assessing potential ecological risks of chemical mixtures and can therefore be useful for catchment‐management decisions. Environ Toxicol Chem 2018;37:715–728. © 2017 The Authors. Environmental Toxicology Chemistry Published by Wiley Periodicals, Inc. PMID:28845901

Nebulisation of corticosteroid suspensions and solutions with a beta(2) agonist.

PubMed

O'Callaghan, Christopher L; White, Judy A; Jackson, Judith M; Barry, Peter W; Kantar, Ahmad

2008-05-01

The aim of this study was to determine the output of salbutamol nebulised in combination with either flunisolide or beclometasone dipropionate (BDP) from two different nebulisers under simulated breathing conditions. The BimboNeb and Nebula nebulisers were used to nebulise 3.0 mL of the two drug mixtures (salbutamol, 5000 microg plus either flunisolide, 600 microg, or BDP, 800 microg). Particle size was determined by inertial impaction. Total outputs of all drugs from both nebulisers were measured using a sinus flow pump under simulated paediatric and adult breathing patterns. The mass median aerodynamic diameter (MMAD) of BDP particles from the mixture was 6.34 mum using the BimboNeb and 5.34 mum using the Nebula. Values for salbutamol in this mixture were 3.93 and 3.32 microm, respectively. The MMAD of flunisolide particles from the BimboNeb and Nebula were 3.74 and 3.65 microm, respectively, while for salbutamol were 3.79 and 3.74 microm, respectively. With the simulated adult breathing pattern, all drug outputs from both mixtures were greater from the BimboNeb than from the Nebula after 5 and 10 min' nebulisation. Drug delivery from the BimboNeb, but not the Nebula, was affected by the simulated breathing pattern. Outputs with the BimboNeb were lower with the paediatric breathing pattern than with the adult pattern. In the majority of cases, nebulising for 10 min produced significantly greater drug output than after 5 min. For the Nebula, outputs were generally similar at 5 and 10 min, irrespective of the breathing pattern. These results highlight the need to assess the amount of aerosolised drug available when drugs are combined, when different nebulisers are used and when they are used with patients of different ages.

Flow pattern changes influenced by variation of viscosities of a heterogeneous gas-liquid mixture flow in a vertical channel

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

Keska, Jerry K.; Hincapie, Juan; Jones, Richard

In the steady-state flow of a heterogeneous mixture such as an air-liquid mixture, the velocity and void fraction are space- and time-dependent parameters. These parameters are the most fundamental in the analysis and description of a multiphase flow. The determination of flow patterns in an objective way is extremely critical, since this is directly related to sudden changes in spatial and temporal changes of the random like characteristic of concentration. Flow patterns can be described by concentration signals in time, amplitude, and frequency domains. Despite the vital importance and countless attempts to solve or incorporate the flow pattern phenomena intomore » multiphase models, it has still been a very challenging topic in the scientific community since the 1940's and has not yet reached a satisfactory solution. This paper reports the experimental results of the impact of fluid viscosity on flow patterns for two-phase flow. Two-phase flow was created in laboratory equipment using air and liquid as phase medium. The liquid properties were changed by using variable concentrations of glycerol in water mixture which generated a wide-range of dynamic viscosities ranging from 1 to 1060 MPa s. The in situ spatial concentration vs. liquid viscosity and airflow velocity of two-phase flow in a vertical ID=50.8 mm pipe were measured using two concomitant computer-aided measurement systems. After acquiring data, the in situ special concentration signals were analyzed in time (spatial concentration and RMS of spatial concentration vs. time), amplitude (PDF and CPDF), and frequency (PSD and CPSD) domains that documented broad flow pattern changes caused by the fluid viscosity and air velocity changes. (author)« less

Application of DNA Machineries for the Barcode Patterned Detection of Genes or Proteins.

PubMed

Zhou, Zhixin; Luo, Guofeng; Wulf, Verena; Willner, Itamar

2018-06-05

The study introduces an analytical platform for the detection of genes or aptamer-ligand complexes by nucleic acid barcode patterns generated by DNA machineries. The DNA machineries consist of nucleic acid scaffolds that include specific recognition sites for the different genes or aptamer-ligand analytes. The binding of the analytes to the scaffolds initiate, in the presence of the nucleotide mixture, a cyclic polymerization/nicking machinery that yields displaced strands of variable lengths. The electrophoretic separation of the resulting strands provides barcode patterns for the specific detection of the different analytes. Mixtures of DNA machineries that yield, upon sensing of different genes (or aptamer ligands), one-, two-, or three-band barcode patterns are described. The combination of nucleic acid scaffolds acting, in the presence of polymerase/nicking enzyme and nucleotide mixture, as DNA machineries, that generate multiband barcode patterns provide an analytical platform for the detection of an individual gene out of many possible genes. The diversity of genes (or other analytes) that can be analyzed by the DNA machineries and the barcode patterned imaging is given by the Pascal's triangle. As a proof-of-concept, the detection of one of six genes, that is, TP53, Werner syndrome, Tay-Sachs normal gene, BRCA1, Tay-Sachs mutant gene, and cystic fibrosis disorder gene by six two-band barcode patterns is demonstrated. The advantages and limitations of the detection of analytes by polymerase/nicking DNA machineries that yield barcode patterns as imaging readout signals are discussed.

Using virtual 3-D plant architecture to assess fungal pathogen splash dispersal in heterogeneous canopies: a case study with cultivar mixtures and a non-specialized disease causal agent

PubMed Central

Gigot, C.; de Vallavieille-Pope, C.; Huber, L.; Saint-Jean, S.

2014-01-01

Background and Aims Recent developments in plant disease management have led to a growing interest in alternative strategies, such as increasing host diversity and decreasing the use of pesticides. Use of cultivar mixtures is one option, allowing the spread of plant epidemics to be slowed down. As dispersal of fungal foliar pathogens over short distances by rain-splash droplets is a major contibutor to the spread of disease, this study focused on modelling the physical mechanisms involved in dispersal of a non-specialized pathogen within heterogeneous canopies of cultivar mixtures, with the aim of optimizing host diversification at the intra-field level. Methods Virtual 3-D wheat-like plants (Triticum aestivum) were used to consider interactions between plant architecture and disease progression in heterogeneous canopies. A combined mechanistic and stochastic model, taking into account splash droplet dispersal and host quantitative resistance within a 3-D heterogeneous canopy, was developed. It consists of four sub-models that describe the spatial patterns of two cultivars within a complex canopy, the pathway of rain-splash droplets within this canopy, the proportion of leaf surface area impacted by dispersal via the droplets and the progression of disease severity after each dispersal event. Key Results Different spatial organization, proportions and resistance levels of the cultivars of two-component mixtures were investigated. For the eight spatial patterns tested, the protective effect against disease was found to vary by almost 2-fold, with the greatest effect being obtained with the smallest genotype unit area, i.e. the ground area occupied by an independent unit of the host population that is genetically homogeneous. Increasing both the difference between resistance levels and the proportion of the most resistant cultivar often resulted in a greater protective effect; however, this was not observed for situations in which the most resistant of the two cultivars in the mixture had a relatively low level of resistance. Conclusions The results show agreement with previous data obtained using experimental approaches. They demonstrate that in order to maximize the potential mixture efficiency against a splash-dispersed pathogen, optimal susceptible/resistant cultivar proportions (ranging from 1/9 to 5/5) have to be established based on host resistance levels. The results also show that taking into account dispersal processes in explicit 3-D plant canopies can be a key tool for investigating disease progression in heterogeneous canopies such as cultivar mixtures. PMID:24989786

Cold-development tool and technique for the ultimate resolution of ZEP520A to fabricate an EB master mold for nano-imprint lithography for 1Tbit/inch2 BPM development

NASA Astrophysics Data System (ADS)

Kobayashi, Hideo; Iyama, Hiromasa; Kagatsume, Takeshi; Watanabe, Tsuyoshi

2012-11-01

Cold-development is well-known for resolution enhancement on ZEP520A. Dipping a wafer in a developer solvent chilled by a freezer, such a typical method had been employed. But, it is obvious that the dip-development method has several inferiorities such as developer temperature instability, temperature inconsistency between developer and a wafer, water-condensation on drying. We then built a single wafer spin-develop tool, and established a process sequence, to solve those difficulties. And, we tried to see their effect down to -10degC over various developers. In specific, we tried to make hole patterns in hexagonal closest packing in 40nm, 35nm, 30nm, 25nm pitch, and examined holes pattern quality and resolution limit by varying setting temperature from room temperature to -10degC in the cold-development, as well as varying developer chemistry from the standard developer ZED N-50 (n-amyl acetate, 100%) to MiBK and IPA mixture which was a rinsing solvent mixture originally. We also examined the other developer (poor solvent mixture) we designed, N-50 and fluorocarbon (FC) mixture, MiBK and FC mixture, and IPA+FC mixture. This paper describes cold-development tool and technique, and its results down to minus (-) 10degC, for ZEP520A resolution enhancement to obtain 1Xnm bits (holes) in 25nm pitch to fabricate an EB master mold for Nano-Imprinting Lithography for 1Tbit/in2 bit patterned media (BPM) in HDD development and production.

Inactivity periods and postural change speed can explain atypical postural change patterns of Caenorhabditis elegans mutants.

PubMed

Fukunaga, Tsukasa; Iwasaki, Wataru

2017-01-19

With rapid advances in genome sequencing and editing technologies, systematic and quantitative analysis of animal behavior is expected to be another key to facilitating data-driven behavioral genetics. The nematode Caenorhabditis elegans is a model organism in this field. Several video-tracking systems are available for automatically recording behavioral data for the nematode, but computational methods for analyzing these data are still under development. In this study, we applied the Gaussian mixture model-based binning method to time-series postural data for 322 C. elegans strains. We revealed that the occurrence patterns of the postural states and the transition patterns among these states have a relationship as expected, and such a relationship must be taken into account to identify strains with atypical behaviors that are different from those of wild type. Based on this observation, we identified several strains that exhibit atypical transition patterns that cannot be fully explained by their occurrence patterns of postural states. Surprisingly, we found that two simple factors-overall acceleration of postural movement and elimination of inactivity periods-explained the behavioral characteristics of strains with very atypical transition patterns; therefore, computational analysis of animal behavior must be accompanied by evaluation of the effects of these simple factors. Finally, we found that the npr-1 and npr-3 mutants have similar behavioral patterns that were not predictable by sequence homology, proving that our data-driven approach can reveal the functions of genes that have not yet been characterized. We propose that elimination of inactivity periods and overall acceleration of postural change speed can explain behavioral phenotypes of strains with very atypical postural transition patterns. Our methods and results constitute guidelines for effectively finding strains that show "truly" interesting behaviors and systematically uncovering novel gene functions by bioimage-informatic approaches.

Thermo-solutal and kinetic modes of stable dendritic growth with different symmetries of crystalline anisotropy in the presence of convection

NASA Astrophysics Data System (ADS)

Alexandrov, Dmitri V.; Galenko, Peter K.; Toropova, Lyubov V.

2018-01-01

Motivated by important applications in materials science and geophysics, we consider the steady-state growth of anisotropic needle-like dendrites in undercooled binary mixtures with a forced convective flow. We analyse the stable mode of dendritic evolution in the case of small anisotropies of growth kinetics and surface energy for arbitrary Péclet numbers and n-fold symmetry of dendritic crystals. On the basis of solvability and stability theories, we formulate a selection criterion giving a stable combination between dendrite tip diameter and tip velocity. A set of nonlinear equations consisting of the solvability criterion and undercooling balance is solved analytically for the tip velocity V and tip diameter ρ of dendrites with n-fold symmetry in the absence of convective flow. The case of convective heat and mass transfer mechanisms in a binary mixture occurring as a result of intensive flows in the liquid phase is detailed. A selection criterion that describes such solidification conditions is derived. The theory under consideration comprises previously considered theoretical approaches and results as limiting cases. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'.

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

USGS Publications Warehouse

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

2013-01-01

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

Coastal Seabed Mapping with Hyperspectral and Lidar data

NASA Astrophysics Data System (ADS)

Taramelli, A.; Valentini, E.; Filipponi, F.; Cappucci, S.

2017-12-01

A synoptic view of the coastal seascape and its dynamics needs a quantitative ability to dissect different components over the complexity of the seafloor where a mixture of geo - biological facies determines geomorphological features and their coverage. The present study uses an analytical approach that takes advantage of a multidimensional model to integrate different data sources from airborne Hyperspectral and LiDAR remote sensing and in situ measurements to detect antropogenic features and ecological `tipping points' in coastal seafloors. The proposed approach has the ability to generate coastal seabed maps using: 1) a multidimensional dataset to account for radiometric and morphological properties of waters and the seafloor; 2) a field spectral library to assimilate the high environmental variability into the multidimensional model; 3) a final classification scheme to represent the spatial gradients in the seafloor. The spatial pattern of the response to anthropogenic forcing may be indistinguishable from patterns of natural variability. It is argued that this novel approach to define tipping points following anthropogenic impacts could be most valuable in the management of natural resources and the economic development of coastal areas worldwide. Examples are reported from different sites of the Mediterranean Sea, both from Marine Protected and un-Protected Areas.

Mixture modeling methods for the assessment of normal and abnormal personality, part II: longitudinal models.

PubMed

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Studying personality and its pathology as it changes, develops, or remains stable over time offers exciting insight into the nature of individual differences. Researchers interested in examining personal characteristics over time have a number of time-honored analytic approaches at their disposal. In recent years there have also been considerable advances in person-oriented analytic approaches, particularly longitudinal mixture models. In this methodological primer we focus on mixture modeling approaches to the study of normative and individual change in the form of growth mixture models and ipsative change in the form of latent transition analysis. We describe the conceptual underpinnings of each of these models, outline approaches for their implementation, and provide accessible examples for researchers studying personality and its assessment.

Effects of grinding and humidification on the transformation of conglomerate to racemic compound in optically active drugs.

PubMed

Piyarom, S; Yonemochi, E; Oguchi, T; Yamamoto, K

1997-04-01

The effects of grinding and humidification on the transformation of conglomerate to racemic compound have been investigated by X-ray powder diffraction (XPD), differential scanning calorimetry (DSC) and infrared (IR) spectroscopy for leucine, norleucine, valine, serine, tartaric acid and malic acid. Racemic physical mixtures were prepared by physical mixing of equimolar quantities of D and I. crystals using a mortar and pestle. Ground mixtures were obtained by grinding the physical mixtures with a vibrational mill. Humidification was performed by storing the physical mixtures and the ground mixtures in a desiccator containing saturated aqueous salt solutions at 40 degrees C. When physical mixtures of malic acid, tartaric acid and serine were ground, the XPD peaks of the racemic compounds were observed. The XPD patterns of humidified physical mixtures of these compounds also showed the formation of the racemic compounds. This indicated that grinding or humidification of malic acid, tartaric acid and serine induced the transformation of conglomerate to racemic compound crystals. When, on the other hand, the physical mixtures of valine, leucine and norleucine were ground, peaks of racemic compounds were not detected in the XPD pattern. After humidification of the ground mixtures of valine, leucine and norleucine, however, the XPD peaks of racemic compounds were observed. DSC and IR studies revealed consistent results. We concluded that grinding or humidification of malic acid, tartaric acid and serine could induce the transformation of a conglomerate to racemic compound. In contrast, humidifying after grinding was needed to bring about the transformation in leucine, norleucine and valine.

Modeling and clustering water demand patterns from real-world smart meter data

NASA Astrophysics Data System (ADS)

Cheifetz, Nicolas; Noumir, Zineb; Samé, Allou; Sandraz, Anne-Claire; Féliers, Cédric; Heim, Véronique

2017-08-01

Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR), a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix) model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN) in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

Contrasting plant height can improve the control of rain-borne diseases in wheat cultivar mixture: modelling splash dispersal in 3-D canopies.

PubMed

Vidal, T; Gigot, C; de Vallavieille-Pope, C; Huber, L; Saint-Jean, S

2018-06-08

Growing cultivars differing by their disease resistance level together (cultivar mixtures) can reduce the propagation of diseases. Although architectural characteristics of cultivars are little considered in mixture design, they could have an effect on disease, in particular through spore dispersal by rain splash, which occurs over short distances. The objective of this work was to assess the impact of plant height of wheat cultivars in mixtures on splash dispersal of Zymoseptoria tritici, which causes septoria tritici leaf blotch. We used a modelling approach involving an explicit description of canopy architecture and splash dispersal processes. The dispersal model computed raindrop interception by a virtual canopy as well as the production, transport and interception of splash droplets carrying inoculum. We designed 3-D virtual canopies composed of susceptible and resistant plants, according to field measurements at the flowering stage. In numerical experiments, we tested different heights of virtual cultivars making up binary mixtures to assess the influence of this architectural trait on dispersal patterns of spore-carrying droplets. Inoculum interception decreased exponentially with the height relative to the main inoculum source (lower diseased leaves of susceptible plants), and little inoculum was intercepted further than 40 cm above the inoculum source. Consequently, tall plants intercepted less inoculum than smaller ones. Plants with twice the standard height intercepted 33 % less inoculum than standard height plants. In cases when the height of suscpeptible plants was doubled, inoculum interception by resistant leaves was 40 % higher. This physical barrier to spore-carrying droplet trajectories reduced inoculum interception by tall susceptible plants and was modulated by plant height differences between cultivars of a binary mixture. These results suggest that mixture effects on spore dispersal could be modulated by an adequate choice of architectural characteristics of cultivars. In particular, even small differences in plant height could reduce spore dispersal.

A simple approach to polymer mixture miscibility.

PubMed

Higgins, Julia S; Lipson, Jane E G; White, Ronald P

2010-03-13

Polymeric mixtures are important materials, but the control and understanding of mixing behaviour poses problems. The original Flory-Huggins theoretical approach, using a lattice model to compute the statistical thermodynamics, provides the basic understanding of the thermodynamic processes involved but is deficient in describing most real systems, and has little or no predictive capability. We have developed an approach using a lattice integral equation theory, and in this paper we demonstrate that this not only describes well the literature data on polymer mixtures but allows new insights into the behaviour of polymers and their mixtures. The characteristic parameters obtained by fitting the data have been successfully shown to be transferable from one dataset to another, to be able to correctly predict behaviour outside the experimental range of the original data and to allow meaningful comparisons to be made between different polymer mixtures.

Stabilization of the Thermal Decomposition of Poly(Propylene Carbonate) Through Copper Ion Incorporation and Use in Self-Patterning

NASA Astrophysics Data System (ADS)

Spencer, Todd J.; Chen, Yu-Chun; Saha, Rajarshi; Kohl, Paul A.

2011-06-01

Incorporation of copper ions into poly(propylene carbonate) (PPC) films cast from γ-butyrolactone (GBL), trichloroethylene (TCE) or methylene chloride (MeCl) solutions containing a photo-acid generator is shown to stabilize the PPC from thermal decomposition. Copper ions were introduced into the PPC mixtures by bringing the polymer mixture into contact with copper metal. The metal was oxidized and dissolved into the PPC mixture. The dissolved copper interferes with the decomposition mechanism of PPC, raising its decomposition temperature. Thermogravimetric analysis shows that copper ions make PPC more stable by up to 50°C. Spectroscopic analysis indicates that copper ions may stabilize terminal carboxylic acid groups, inhibiting PPC decomposition. The change in thermal stability based on PPC exposure to patterned copper substrates was used to provide a self-aligned patterning method for PPC on copper traces without the need for an additional photopatterning registration step. Thermal decomposition of PPC is then used to create air isolation regions around the copper traces. The spatial resolution of the self-patterning PPC process is limited by the lateral diffusion of the copper ions within the PPC. The concentration profiles of copper within the PPC, patterning resolution, and temperature effects on the PPC decomposition have been studied.

Solubility enhancement of miconazole nitrate: binary and ternary mixture approach.

PubMed

Rai, Vineet Kumar; Dwivedi, Harinath; Yadav, Narayan Prasad; Chanotiya, Chandan Singh; Saraf, Shubhini A

2014-08-01

Enhancement of aqueous solubility of very slightly soluble Miconazole Nitrate (MN) is required to widen its application from topical formulation to oral/mucoadhesive formulations. Aim of the present investigation was to enhance the aqueous solubility of MN using binary and ternary mixture approach. Binary mixtures such as solvent deposition, inclusion complexation and solid dispersion were adopted to enhance solubility using different polymers like lactose, beta-cyclodextrin (β-CD) and polyethylene-glycol 6000 (PEG 6000), respectively. Batches of binary mixtures with highest solubility enhancement potentials were further mixed to form ternary mixture by a simple kneading method. Drug polymer interaction and mixture morphology was studied using the Fourier transform infrared spectroscopy and the scanning electron microscopy, respectively along with their saturation solubility studies and drug release. An excellent solubility enhancement, i.e. up to 72 folds and 316 folds of MN was seen by binary and ternary mixture, respectively. Up to 99.5% drug was released in 2 h from the mixtures of MN and polymers. RESULTS revealed that solubility enhancement by binary mixtures is achieved due to surface modification and by increasing wettability of MN. Tremendous increase in solubility of MN by ternary mixture could possibly be due to blending of water soluble polymers, i.e. lactose and PEG 6000 with β-CD which was found to enhance the solubilizing nature of β-CD. Owing to the excellent solubility enhancement potential of ternary mixtures in enhancing MN solubility from 110.4 μg/ml to 57640.0 μg/ml, ternary mixture approach could prove to be promising in the development of oral/mucoadhesive formulations.

MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

EPA Science Inventory

Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

Fuzzy membership functions for analysis of high-resolution CT images of diffuse pulmonary diseases.

PubMed

Almeida, Eliana; Rangayyan, Rangaraj M; Azevedo-Marques, Paulo M

2015-08-01

We propose the use of fuzzy membership functions to analyze images of diffuse pulmonary diseases (DPDs) based on fractal and texture features. The features were extracted from preprocessed regions of interest (ROIs) selected from high-resolution computed tomography images. The ROIs represent five different patterns of DPDs and normal lung tissue. A Gaussian mixture model (GMM) was constructed for each feature, with six Gaussians modeling the six patterns. Feature selection was performed and the GMMs of the five significant features were used. From the GMMs, fuzzy membership functions were obtained by a probability-possibility transformation and further statistical analysis was performed. An average classification accuracy of 63.5% was obtained for the six classes. For four of the six classes, the classification accuracy was superior to 65%, and the best classification accuracy was 75.5% for one class. The use of fuzzy membership functions to assist in pattern classification is an alternative to deterministic approaches to explore strategies for medical diagnosis.

A Stochastic-Variational Model for Soft Mumford-Shah Segmentation

PubMed Central

2006-01-01

In contemporary image and vision analysis, stochastic approaches demonstrate great flexibility in representing and modeling complex phenomena, while variational-PDE methods gain enormous computational advantages over Monte Carlo or other stochastic algorithms. In combination, the two can lead to much more powerful novel models and efficient algorithms. In the current work, we propose a stochastic-variational model for soft (or fuzzy) Mumford-Shah segmentation of mixture image patterns. Unlike the classical hard Mumford-Shah segmentation, the new model allows each pixel to belong to each image pattern with some probability. Soft segmentation could lead to hard segmentation, and hence is more general. The modeling procedure, mathematical analysis on the existence of optimal solutions, and computational implementation of the new model are explored in detail, and numerical examples of both synthetic and natural images are presented. PMID:23165059

Patterning in systems driven by nonlocal external forces.

PubMed

Luneville, L; Mallick, K; Pontikis, V; Simeone, D

2016-11-01

This work focuses on systems displaying domain patterns resulting from competing external and internal dynamics. To this end, we introduce a Lyapunov functional capable of describing the steady states of systems subject to external forces, by adding nonlocal terms to the Landau Ginzburg free energy of the system. Thereby, we extend the existing methodology treating long-range order interactions, to the case of external nonlocal forces. By studying the quadratic term of this Lyapunov functional, we compute the phase diagram in the temperature versus external field and we determine all possible modulated phases (domain patterns) as a function of the external forces and the temperature. Finally, we investigate patterning in chemical reactive mixtures and binary mixtures under irradiation, and we show that the last case opens the path toward micro-structural engineering of materials.

Patterning in systems driven by nonlocal external forces

NASA Astrophysics Data System (ADS)

Luneville, L.; Mallick, K.; Pontikis, V.; Simeone, D.

2016-11-01

This work focuses on systems displaying domain patterns resulting from competing external and internal dynamics. To this end, we introduce a Lyapunov functional capable of describing the steady states of systems subject to external forces, by adding nonlocal terms to the Landau Ginzburg free energy of the system. Thereby, we extend the existing methodology treating long-range order interactions, to the case of external nonlocal forces. By studying the quadratic term of this Lyapunov functional, we compute the phase diagram in the temperature versus external field and we determine all possible modulated phases (domain patterns) as a function of the external forces and the temperature. Finally, we investigate patterning in chemical reactive mixtures and binary mixtures under irradiation, and we show that the last case opens the path toward micro-structural engineering of materials.

Noise-induced escape in an excitable system

NASA Astrophysics Data System (ADS)

Khovanov, I. A.; Polovinkin, A. V.; Luchinsky, D. G.; McClintock, P. V. E.

2013-03-01

We consider the stochastic dynamics of escape in an excitable system, the FitzHugh-Nagumo (FHN) neuronal model, for different classes of excitability. We discuss, first, the threshold structure of the FHN model as an example of a system without a saddle state. We then develop a nonlinear (nonlocal) stability approach based on the theory of large fluctuations, including a finite-noise correction, to describe noise-induced escape in the excitable regime. We show that the threshold structure is revealed via patterns of most probable (optimal) fluctuational paths. The approach allows us to estimate the escape rate and the exit location distribution. We compare the responses of a monostable resonator and monostable integrator to stochastic input signals and to a mixture of periodic and stochastic stimuli. Unlike the commonly used local analysis of the stable state, our nonlocal approach based on optimal paths yields results that are in good agreement with direct numerical simulations of the Langevin equation.

A Statistical Approach for Judging Stability of Whole Mixture Chemical Composition over Time for Highly Complex Disinfection By-Product Mixtures from EPA's Four Lab Study

EPA Science Inventory

Chemical characterization of complex mixtures and assessment of stability over time of the characterized chemicals is crucial both to characterize exposure and to use data from one mixture as a surrogate for other similar mixtures. The chemical composition of test mixtures can va...

Identification of Allelic Imbalance with a Statistical Model for Subtle Genomic Mosaicism

PubMed Central

Xia, Rui; Vattathil, Selina; Scheet, Paul

2014-01-01

Genetic heterogeneity in a mixed sample of tumor and normal DNA can confound characterization of the tumor genome. Numerous computational methods have been proposed to detect aberrations in DNA samples from tumor and normal tissue mixtures. Most of these require tumor purities to be at least 10–15%. Here, we present a statistical model to capture information, contained in the individual's germline haplotypes, about expected patterns in the B allele frequencies from SNP microarrays while fully modeling their magnitude, the first such model for SNP microarray data. Our model consists of a pair of hidden Markov models—one for the germline and one for the tumor genome—which, conditional on the observed array data and patterns of population haplotype variation, have a dependence structure induced by the relative imbalance of an individual's inherited haplotypes. Together, these hidden Markov models offer a powerful approach for dealing with mixtures of DNA where the main component represents the germline, thus suggesting natural applications for the characterization of primary clones when stromal contamination is extremely high, and for identifying lesions in rare subclones of a tumor when tumor purity is sufficient to characterize the primary lesions. Our joint model for germline haplotypes and acquired DNA aberration is flexible, allowing a large number of chromosomal alterations, including balanced and imbalanced losses and gains, copy-neutral loss-of-heterozygosity (LOH) and tetraploidy. We found our model (which we term J-LOH) to be superior for localizing rare aberrations in a simulated 3% mixture sample. More generally, our model provides a framework for full integration of the germline and tumor genomes to deal more effectively with missing or uncertain features, and thus extract maximal information from difficult scenarios where existing methods fail. PMID:25166618

Plasma Jet Printing and in Situ Reduction of Highly Acidic Graphene Oxide.

PubMed

Dey, Avishek; Krishnamurthy, Satheesh; Bowen, James; Nordlund, Dennis; Meyyappan, M; Gandhiraman, Ram P

2018-05-23

Miniaturization of electronic devices and the advancement of Internet of Things pose exciting challenges to develop technologies for patterned deposition of functional nanomaterials. Printed and flexible electronic devices and energy storage devices can be embedded onto clothing or other flexible surfaces. Graphene oxide (GO) has gained much attention in printed electronics due its solution processability, robustness, and high electrical conductivity in the reduced state. Here, we introduce an approach to print GO films from highly acidic suspensions with in situ reduction using an atmospheric pressure plasma jet. Low-temperature plasma of a He and H 2 mixture was used successfully to reduce a highly acidic GO suspension (pH < 2) in situ during deposition. This technique overcomes the multiple intermediate steps required to increase the conductivity of deposited GO. X-ray spectroscopic studies confirmed that the reaction intermediates and the concentration of oxygen functionalities bonded to GO have been reduced significantly by this approach without any additional steps. Moreover, the reduced GO films showed enhanced conductivity. Hence, this technique has a strong potential for printing conducting patterns of GO for a range of large-scale applications.

Phase-coexisting patterns, horizontal segregation, and controlled convection in vertically vibrated binary granular mixtures

NASA Astrophysics Data System (ADS)

Ansari, Istafaul Haque; Rivas, Nicolas; Alam, Meheboob

2018-01-01

We report patterns consisting of coexistence of synchronous and asynchronous states [for example, a granular gas co-existing with (i) bouncing bed, (ii) undulatory subharmonic waves, and (iii) Leidenfrost-like states] in experiments on vertically vibrated binary granular mixtures in a Hele-Shaw cell. Most experiments have been carried out with equimolar binary mixtures of glass and steel balls of same diameter by varying the total layer height (F ) for a range of shaking acceleration (Γ ). All patterns as well as the related phase diagram in the (Γ ,F ) plane have been reproduced via molecular dynamics simulations of the same system. The segregation of heavier and lighter particles along the horizontal direction is shown to be the progenitor of such phase-coexisting patterns as confirmed in both experiment and simulation. At strong shaking we uncover a partial convection state in which a pair of convection rolls is found to coexist with a Leidenfrost-like state. The crucial role of the relative number density of two species on controlling the buoyancy-driven granular convection is demonstrated. The onset of horizontal segregation can be explained in terms of an anisotropic diffusion tensor.

PACE: Probabilistic Assessment for Contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures.

PubMed

Marciano, Michael A; Adelman, Jonathan D

2017-03-01

The deconvolution of DNA mixtures remains one of the most critical challenges in the field of forensic DNA analysis. In addition, of all the data features required to perform such deconvolution, the number of contributors in the sample is widely considered the most important, and, if incorrectly chosen, the most likely to negatively influence the mixture interpretation of a DNA profile. Unfortunately, most current approaches to mixture deconvolution require the assumption that the number of contributors is known by the analyst, an assumption that can prove to be especially faulty when faced with increasingly complex mixtures of 3 or more contributors. In this study, we propose a probabilistic approach for estimating the number of contributors in a DNA mixture that leverages the strengths of machine learning. To assess this approach, we compare classification performances of six machine learning algorithms and evaluate the model from the top-performing algorithm against the current state of the art in the field of contributor number classification. Overall results show over 98% accuracy in identifying the number of contributors in a DNA mixture of up to 4 contributors. Comparative results showed 3-person mixtures had a classification accuracy improvement of over 6% compared to the current best-in-field methodology, and that 4-person mixtures had a classification accuracy improvement of over 20%. The Probabilistic Assessment for Contributor Estimation (PACE) also accomplishes classification of mixtures of up to 4 contributors in less than 1s using a standard laptop or desktop computer. Considering the high classification accuracy rates, as well as the significant time commitment required by the current state of the art model versus seconds required by a machine learning-derived model, the approach described herein provides a promising means of estimating the number of contributors and, subsequently, will lead to improved DNA mixture interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Opto electronic tweezers based smart sweeper for cells/micro-particles sorting

NASA Astrophysics Data System (ADS)

Verma, R. S.; Kumar, N.

2018-04-01

We report on use of opto-electronic tweezers based sorting approach, termed as smart sweepers, for sorting the microscopic particles by using the Dielectrophoretic (DEP) force response of cells on applied a.c. bias frequency. The applied a.c. bias was kept in negative DEP region, close to the crossover frequency of one of the particles. A line shaped intensity pattern, generated by a cylindrical lens, was scanned across the mixture sample. The particles whose cross over frequency was close to the applied bias frequency, experienced negligible negative DEP(n-DEP) force. On the other hand, the other type of particle experienced large repelling force and were forced to move along the scanning direction of the line shaped intensity profile. We, as a proof of concept, demonstrated the working principle of opto electronic smart sweepers by sweeping out the polystyrene particles from a mixture consisting of polystyrene microspheres (PSM) and red blood cells (RBCs) and leaving RBCs in the region of interest.

Phylogenetic relationships of South American lizards of the genus Stenocercus (Squamata: Iguania): A new approach using a general mixture model for gene sequence data.

PubMed

Torres-Carvajal, Omar; Schulte, James A; Cadle, John E

2006-04-01

The South American iguanian lizard genus Stenocercus includes 54 species occurring mostly in the Andes and adjacent lowland areas from northern Venezuela and Colombia to central Argentina at elevations of 0-4000m. Small taxon or character sampling has characterized all phylogenetic analyses of Stenocercus, which has long been recognized as sister taxon to the Tropidurus Group. In this study, we use mtDNA sequence data to perform phylogenetic analyses that include 32 species of Stenocercus and 12 outgroup taxa. Monophyly of this genus is strongly supported by maximum parsimony and Bayesian analyses. Evolutionary relationships within Stenocercus are further analyzed with a Bayesian implementation of a general mixture model, which accommodates variability in the pattern of evolution across sites. These analyses indicate a basal split of Stenocercus into two clades, one of which receives very strong statistical support. In addition, we test previous hypotheses using non-parametric and parametric statistical methods, and provide a phylogenetic classification for Stenocercus.

Selective Sensing of Gas Mixture via a Temperature Modulation Approach: New Strategy for Potentiometric Gas Sensor Obtaining Satisfactory Discriminating Features

PubMed Central

Li, Fu-an; Jin, Han; Wang, Jinxia; Zou, Jie; Jian, Jiawen

2017-01-01

A new strategy to discriminate four types of hazardous gases is proposed in this research. Through modulating the operating temperature and the processing response signal with a pattern recognition algorithm, a gas sensor consisting of a single sensing electrode, i.e., ZnO/In2O3 composite, is designed to differentiate NO2, NH3, C3H6, CO within the level of 50–400 ppm. Results indicate that with adding 15 wt.% ZnO to In2O3, the sensor fabricated at 900 °C shows optimal sensing characteristics in detecting all the studied gases. Moreover, with the aid of the principle component analysis (PCA) algorithm, the sensor operating in the temperature modulation mode demonstrates acceptable discrimination features. The satisfactory discrimination features disclose the future that it is possible to differentiate gas mixture efficiently through operating a single electrode sensor at temperature modulation mode. PMID:28287492

Downstream lightening and upward heavying, sorting of sediments of uniform grain size but differing in density

NASA Astrophysics Data System (ADS)

Viparelli, E.; Solari, L.; Hill, K. M.

2014-12-01

Downstream fining, i.e. the tendency for a gradual decrease in grain size in the downstream direction, has been observed and studied in alluvial rivers and in laboratory flumes. Laboratory experiments and field observations show that the vertical sorting pattern over a small Gilbert delta front is characterized by an upward fining profile, with preferential deposition of coarse particles in the lowermost part of the deposit. The present work is an attempt to answer the following questions. Are there analogous sorting patterns in mixtures of sediment particles having the same grain size but differing density? To investigate this, we performed experiments at the Hydrosystems Laboratory at the University of Illinois at Urbana-Champaign. During the experiments a Gilbert delta formed and migrated downstream allowing for the study of transport and sorting processes on the surface and within the deposit. The experimental results show 1) preferential deposition of heavy particles in the upstream part of the deposit associated with a pattern of "downstream lightening"; and 2) a vertical sorting pattern over the delta front characterized by a pattern of "upward heavying" with preferential deposition of light particles in the lowermost part of the deposit. The observed downstream lightening is analogous of the downstream fining with preferential deposition of heavy (coarse) particles in the upstream part of the deposit. The observed upward heavying was unexpected because, considering the particle mass alone, the heavy (coarse) particles should have been preferentially deposited in the lowermost part of the deposit. Further, the application of classical fractional bedload transport relations suggests that in the case of mixtures of particles of uniform size and different densities equal mobility is not approached. We hypothesize that granular physics mechanisms traditionally associated with sheared granular flows may be responsible for the observed upward heavying and for the deviation from equal mobility.

Patterning vascular networks in vivo for tissue engineering applications.

PubMed

Chaturvedi, Ritika R; Stevens, Kelly R; Solorzano, Ricardo D; Schwartz, Robert E; Eyckmans, Jeroen; Baranski, Jan D; Stapleton, Sarah Chase; Bhatia, Sangeeta N; Chen, Christopher S

2015-05-01

The ultimate design of functionally therapeutic engineered tissues and organs will rely on our ability to engineer vasculature that can meet tissue-specific metabolic needs. We recently introduced an approach for patterning the formation of functional spatially organized vascular architectures within engineered tissues in vivo. Here, we now explore the design parameters of this approach and how they impact the vascularization of an engineered tissue construct after implantation. We used micropatterning techniques to organize endothelial cells (ECs) into geometrically defined "cords," which in turn acted as a template after implantation for the guided formation of patterned capillaries integrated with the host tissue. We demonstrated that the diameter of the cords before implantation impacts the location and density of the resultant capillary network. Inclusion of mural cells to the vascularization response appears primarily to impact the dynamics of vascularization. We established that clinically relevant endothelial sources such as induced pluripotent stem cell-derived ECs and human microvascular endothelial cells can drive vascularization within this system. Finally, we demonstrated the ability to control the juxtaposition of parenchyma with perfused vasculature by implanting cords containing a mixture of both a parenchymal cell type (hepatocytes) and ECs. These findings define important characteristics that will ultimately impact the design of vasculature structures that meet tissue-specific needs.

Environmental chemical mixtures: Assessing ecological exposure and effects in streams

EPA Science Inventory

This product is a USGS fact sheet that describes a collaborative effort between USGS and US EPA to characterize exposures to chemical mixtures and associated biological effects for a diverse range of US streams representing varying watershed size, land-use patterns, and ecotypes.

Synergy in Protein–Osmolyte Mixtures

PubMed Central

2014-01-01

Virtually all taxa use osmolytes to protect cells against biochemical stress. Osmolytes often occur in mixtures, such as the classical combination of urea with TMAO (trimethylamine N-oxide) in cartilaginous fish or the cocktail of at least six different osmolytes in the kidney. The concentration patterns of osmolyte mixtures found in vivo make it likely that synergy between them plays an important role. Using statistical mechanical n-component Kirkwood–Buff theory, we show from first principles that synergy in protein–osmolyte systems can arise from two separable sources: (1) mutual alteration of protein surface solvation and (2) effects mediated through bulk osmolyte chemical activities. We illustrate both effects in a four-component system with the experimental example of the unfolding of a notch ankyrin domain in urea–TMAO mixtures, which make urea a less effective denaturant and TMAO a more effective stabilizer. Protein surface effects are primarily responsible for this synergy. The specific patterns of surface solvation point to denatured state expansion as the main factor, as opposed to direct competition. PMID:25490052

Optimization of fruit punch using mixture design.

PubMed

Kumar, S Bharath; Ravi, R; Saraswathi, G

2010-01-01

A highly acceptable dehydrated fruit punch was developed with selected fruits, namely lemon, orange, and mango, using a mixture design and optimization technique. The fruit juices were freeze dried, powdered, and used in the reconstitution studies. Fruit punches were prepared according to the experimental design combinations (total 10) based on a mixture design and then subjected to sensory evaluation for acceptability. Response surfaces of sensory attributes were also generated as a function of fruit juices. Analysis of data revealed that the fruit punch prepared using 66% of mango, 33% of orange, and 1% of lemon had highly desirable sensory scores for color (6.00), body (5.92), sweetness (5.68), and pleasantness (5.94). The aroma pattern of individual as well as combinations of fruit juices were also analyzed by electronic nose. The electronic nose could discriminate the aroma patterns of individual as well as fruit juice combinations by mixture design. The results provide information on the sensory quality of best fruit punch formulations liked by the consumer panel based on lemon, orange, and mango.

Decomposition of heterogeneous organic matterand its long-term stabilization in soils

USGS Publications Warehouse

Sierra, Carlos A.; Harmon, Mark E.; Perakis, Steven S.

2011-01-01

Soil organic matter is a complex mixture of material with heterogeneous biological, physical, and chemical properties. Decomposition models represent this heterogeneity either as a set of discrete pools with different residence times or as a continuum of qualities. It is unclear though, whether these two different approaches yield comparable predictions of organic matter dynamics. Here, we compare predictions from these two different approaches and propose an intermediate approach to study organic matter decomposition based on concepts from continuous models implemented numerically. We found that the disagreement between discrete and continuous approaches can be considerable depending on the degree of nonlinearity of the model and simulation time. The two approaches can diverge substantially for predicting long-term processes in soils. Based on our alternative approach, which is a modification of the continuous quality theory, we explored the temporal patterns that emerge by treating substrate heterogeneity explicitly. The analysis suggests that the pattern of carbon mineralization over time is highly dependent on the degree and form of nonlinearity in the model, mostly expressed as differences in microbial growth and efficiency for different substrates. Moreover, short-term stabilization and destabilization mechanisms operating simultaneously result in long-term accumulation of carbon characterized by low decomposition rates, independent of the characteristics of the incoming litter. We show that representation of heterogeneity in the decomposition process can lead to substantial improvements in our understanding of carbon mineralization and its long-term stability in soils.

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.

An EM-based semi-parametric mixture model approach to the regression analysis of competing-risks data.

PubMed

Ng, S K; McLachlan, G J

2003-04-15

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright 2003 John Wiley & Sons, Ltd.

Formation and photopatterning of nanoporous titania thin films

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

Park, Oun-Ho; Cheng, Joy Y.; Kim, Hyun Suk

2007-06-04

Photopatternable nanoporous titania thin films were generated from mixtures of an organic diblock copolymer, poly(styrene-b-ethylene oxide) (PS-b-PEO), and an oligomeric titanate (OT) prepared from a chelated titanium isopropoxide. The PS-b-PEO templates well-defined microdomains in thin films of the mixtures, which upon thermal treatment at 450 deg. C, become nanopores in titania. Average pore size and porosity are controlled by the molecular weight and loading level of the PS-b-PEO, respectively. Patterns of nanoporous titania were created by selectively exposing UV light on the mixture films. The UV irradiation destroys the chelating bond and induces the cross-linking reaction of the OT. Subsequentmore » wet development followed by thermal treatment gives patterned nanoporous films of anatase phase titania.« less

Prescribing Patterns and Safety of Mezclitas for Respiratory Illnesses

PubMed Central

Quevedo, Juan; Marsh, Wallace; Yulfo, Jessica; Alvarez, Olga; Felici, Marcos; Rojas, Maria E

2012-01-01

Objectives To evaluate the prescribing patterns of compound mixtures of cough and cold liquid medications, known as mezclitas, which are prescribed to patients with respiratory illnesses in Puerto Rico. Secondary objectives include assessing the potential safety of these mixtures and patients’ perception of them. Methods Using a cross sectional study approach, a convenience sample was obtained from five pharmacies in Puerto Rico, from October 2008 to October 2009. Patients were asked to complete a 9-item questionnaire of demographic information, in addition to their mezclita prescription data. Results The mean age of patients was 43 years with a range of less than 12 months to 101 years. For children ≤ four years of age, 71% were prescribed cough and cold medications. Sixty-four percent of the prescriptions were given to females. The most prevalent ingredient employed was guaifenesin, which appeared in about 77% of the mezclitas. ‘Common cold’ was the principal diagnosis for 62% of the prescriptions, of which 75% of these prescriptions contained a corticosteroid and 17% contained a beta2 agonist bronchodilator. The top medical prescribing specialty was general medicine (51%). Thirty-eight percent of hypertensive patients were prescribed a decongestant. The majority of diabetic patients (60%) were dispensed a corticosteroid. Most (74%) patients reported that they had a rapid and good response to their mezclita. Conclusion Mezclitas were most commonly prescribed for acute symptoms of upper respiratory illness by general physicians, despite possible side effects. This study suggests that the prescription patterns of mezclitas do not always consider evidence-based medicine treatment guidelines. PMID:23038886

Mixtures and their risk assessment in toxicology.

PubMed

Mumtaz, Moiz M; Hansen, Hugh; Pohl, Hana R

2011-01-01

For communities generally and for persons living in the vicinity of waste sites specifically, potential exposures to chemical mixtures are genuine concerns. Such concerns often arise from perceptions of a site's higher than anticipated toxicity due to synergistic interactions among chemicals. This chapter outlines some historical approaches to mixtures risk assessment. It also outlines ATSDR's current approach to toxicity risk assessment. The ATSDR's joint toxicity assessment guidance for chemical mixtures addresses interactions among components of chemical mixtures. The guidance recommends a series of steps that include simple calculations for a systematic analysis of data leading to conclusions regarding any hazards chemical mixtures might pose. These conclusions can, in turn, lead to recommendations such as targeted research to fill data gaps, development of new methods using current science, and health education to raise awareness of residents and health care providers. The chapter also provides examples of future trends in chemical mixtures assessment.

A Mixtures-of-Trees Framework for Multi-Label Classification

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

We propose a new probabilistic approach for multi-label classification that aims to represent the class posterior distribution P(Y|X). Our approach uses a mixture of tree-structured Bayesian networks, which can leverage the computational advantages of conditional tree-structured models and the abilities of mixtures to compensate for tree-structured restrictions. We develop algorithms for learning the model from data and for performing multi-label predictions using the learned model. Experiments on multiple datasets demonstrate that our approach outperforms several state-of-the-art multi-label classification methods. PMID:25927011

Boundary methods for mode estimation

NASA Astrophysics Data System (ADS)

Pierson, William E., Jr.; Ulug, Batuhan; Ahalt, Stanley C.

1999-08-01

This paper investigates the use of Boundary Methods (BMs), a collection of tools used for distribution analysis, as a method for estimating the number of modes associated with a given data set. Model order information of this type is required by several pattern recognition applications. The BM technique provides a novel approach to this parameter estimation problem and is comparable in terms of both accuracy and computations to other popular mode estimation techniques currently found in the literature and automatic target recognition applications. This paper explains the methodology used in the BM approach to mode estimation. Also, this paper quickly reviews other common mode estimation techniques and describes the empirical investigation used to explore the relationship of the BM technique to other mode estimation techniques. Specifically, the accuracy and computational efficiency of the BM technique are compared quantitatively to the a mixture of Gaussian (MOG) approach and a k-means approach to model order estimation. The stopping criteria of the MOG and k-means techniques is the Akaike Information Criteria (AIC).

Concrete pavement mixture design and analysis (MDA) : an innovative approach to proportioning concrete mixtures.

DOT National Transportation Integrated Search

2015-03-01

Mixture proportioning is routinely a matter of using a recipe based on a previously produced concrete, rather than adjusting the : proportions based on the needs of the mixture and the locally available materials. As budgets grow tighter and increasi...

Chemical Mixture Risk Assessment Additivity-Based Approaches

EPA Science Inventory

Powerpoint presentation includes additivity-based chemical mixture risk assessment methods. Basic concepts, theory and example calculations are included. Several slides discuss the use of "common adverse outcomes" in analyzing phthalate mixtures.

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

Quality improvement of melt extruded laminar systems using mixture design.

PubMed

Hasa, D; Perissutti, B; Campisi, B; Grassi, M; Grabnar, I; Golob, S; Mian, M; Voinovich, D

2015-07-30

This study investigates the application of melt extrusion for the development of an oral retard formulation with a precise drug release over time. Since adjusting the formulation appears to be of the utmost importance in achieving the desired drug release patterns, different formulations of laminar extrudates were prepared according to the principles of Experimental Design, using a design for mixtures to assess the influence of formulation composition on the in vitro drug release from the extrudates after 1h and after 8h. The effect of each component on the two response variables was also studied. Ternary mixtures of theophylline (model drug), monohydrate lactose and microcrystalline wax (as thermoplastic binder) were extruded in a lab scale vertical ram extruder in absence of solvents at a temperature below the melting point of the binder (so that the crystalline state of the drug could be maintained), through a rectangular die to obtain suitable laminar systems. Thanks to the desirability approach and a reliability study for ensuring the quality of the formulation, a very restricted optimal zone was defined within the experimental domain. Among the mixture components, the variation of microcrystalline wax content played the most significant role in overall influence on the in vitro drug release. The formulation theophylline:lactose:wax, 57:14:29 (by weight), selected based on the desirability zone, was subsequently used for in vivo studies. The plasma profile, obtained after oral administration of the laminar extruded system in hard gelatine capsules, revealed the typical trend of an oral retard formulation. The application of the mixture experimental design associated to a desirability function permitted to optimize the extruded system and to determine the composition space that ensures final product quality. Copyright © 2015 Elsevier B.V. All rights reserved.

A statistical approach to optimizing concrete mixture design.

PubMed

Ahmad, Shamsad; Alghamdi, Saeid A

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (3(3)). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m(3)), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

A Statistical Approach to Optimizing Concrete Mixture Design

PubMed Central

Alghamdi, Saeid A.

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (33). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m3), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options. PMID:24688405

A fast flexible ink-jet printing method for patterning dissociated neurons in culture.

PubMed

Sanjana, Neville E; Fuller, Sawyer B

2004-07-30

We present a new technique that uses a custom-built ink-jet printer to fabricate precise micropatterns of cell adhesion materials for neural cell culture. Other work in neural cell patterning has employed photolithography or "soft lithographic" techniques such as micro-stamping, but such approaches are limited by their use of an un-alterable master pattern such as a mask or stamp master and can be resource-intensive. In contrast, ink-jet printing, used in low-cost desktop printers, patterns material by depositing microscopic droplets under robotic control in a programmable and inexpensive manner. We report the use of ink-jet printing to fabricate neuron-adhesive patterns such as islands and other shapes using poly(ethylene) glycol as the cell-repulsive material and a collagen/poly-D-lysine (PDL) mixture as the cell-adhesive material. We show that dissociated rat hippocampal neurons and glia grown at low densities on such patterns retain strong pattern adherence for over 25 days. The patterned neurons are comparable to control, un-patterned cells in electrophysiological properties and in immunocytochemical measurements of synaptic density and inhibitory cell distributions. We suggest that an inexpensive desktop printer may be an accessible tool for making micro-island cultures and other basic patterns. We also suggest that ink-jet printing may be extended to a range of developmental neuroscience studies, given its ability to more easily layer materials, build substrate-bound gradients, construct out-of-plane structure, and deposit sources of diffusible factors. Copyright 2004 Elsevier B.V.

Using virtual 3-D plant architecture to assess fungal pathogen splash dispersal in heterogeneous canopies: a case study with cultivar mixtures and a non-specialized disease causal agent.

PubMed

Gigot, C; de Vallavieille-Pope, C; Huber, L; Saint-Jean, S

2014-09-01

Recent developments in plant disease management have led to a growing interest in alternative strategies, such as increasing host diversity and decreasing the use of pesticides. Use of cultivar mixtures is one option, allowing the spread of plant epidemics to be slowed down. As dispersal of fungal foliar pathogens over short distances by rain-splash droplets is a major contibutor to the spread of disease, this study focused on modelling the physical mechanisms involved in dispersal of a non-specialized pathogen within heterogeneous canopies of cultivar mixtures, with the aim of optimizing host diversification at the intra-field level. Virtual 3-D wheat-like plants (Triticum aestivum) were used to consider interactions between plant architecture and disease progression in heterogeneous canopies. A combined mechanistic and stochastic model, taking into account splash droplet dispersal and host quantitative resistance within a 3-D heterogeneous canopy, was developed. It consists of four sub-models that describe the spatial patterns of two cultivars within a complex canopy, the pathway of rain-splash droplets within this canopy, the proportion of leaf surface area impacted by dispersal via the droplets and the progression of disease severity after each dispersal event. Different spatial organization, proportions and resistance levels of the cultivars of two-component mixtures were investigated. For the eight spatial patterns tested, the protective effect against disease was found to vary by almost 2-fold, with the greatest effect being obtained with the smallest genotype unit area, i.e. the ground area occupied by an independent unit of the host population that is genetically homogeneous. Increasing both the difference between resistance levels and the proportion of the most resistant cultivar often resulted in a greater protective effect; however, this was not observed for situations in which the most resistant of the two cultivars in the mixture had a relatively low level of resistance. The results show agreement with previous data obtained using experimental approaches. They demonstrate that in order to maximize the potential mixture efficiency against a splash-dispersed pathogen, optimal susceptible/resistant cultivar proportions (ranging from 1/9 to 5/5) have to be established based on host resistance levels. The results also show that taking into account dispersal processes in explicit 3-D plant canopies can be a key tool for investigating disease progression in heterogeneous canopies such as cultivar mixtures. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

High/variable mixture ratio O2/H2 engine

NASA Technical Reports Server (NTRS)

Adams, A.; Parsley, R. C.

1988-01-01

Vehicle/engine analysis studies have identified the High/Dual Mixture Ratio O2/H2 Engine cycle as a leading candidate for an advanced Single Stage to Orbit (SSTO) propulsion system. This cycle is designed to allow operation at a higher than normal O/F ratio of 12 during liftoff and then transition to a more optimum O/F ratio of 6 at altitude. While operation at high mixture ratios lowers specific impulse, the resultant high propellant bulk density and high power density combine to minimize the influence of atmospheric drag and low altitude gravitational forces. Transition to a lower mixture ratio at altitude then provides improved specific impulse relative to a single mixture ratio engine that must select a mixture ratio that is balanced for both low and high altitude operation. This combination of increased altitude specific impulse and high propellant bulk density more than offsets the compromised low altitude performance and results in an overall mission benefit. Two areas of technical concern relative to the execution of this dual mixture ratio cycle concept are addressed. First, actions required to transition from high to low mixture ratio are examined, including an assessment of the main chamber environment as the main chamber mixture ratio passes through stoichiometric. Secondly, two approaches to meet a requirement for high turbine power at high mixture ratio condition are examined. One approach uses high turbine temperature to produce the power and requires cooled turbines. The other approach incorporates an oxidizer-rich preburner to increase turbine work capability via increased turbine mass flow.

Spectral pattern recognition of controlled substances in street samples using artificial neural network system

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

2011-04-01

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Protein recognition by a pattern-generating fluorescent molecular probe.

PubMed

Pode, Zohar; Peri-Naor, Ronny; Georgeson, Joseph M; Ilani, Tal; Kiss, Vladimir; Unger, Tamar; Markus, Barak; Barr, Haim M; Motiei, Leila; Margulies, David

2017-12-01

Fluorescent molecular probes have become valuable tools in protein research; however, the current methods for using these probes are less suitable for analysing specific populations of proteins in their native environment. In this study, we address this gap by developing a unimolecular fluorescent probe that combines the properties of small-molecule-based probes and cross-reactive sensor arrays (the so-called chemical 'noses/tongues'). On the one hand, the probe can detect different proteins by generating unique identification (ID) patterns, akin to cross-reactive arrays. On the other hand, its unimolecular scaffold and selective binding enable this ID-generating probe to identify combinations of specific protein families within complex mixtures and to discriminate among isoforms in living cells, where macroscopic arrays cannot access. The ability to recycle the molecular device and use it to track several binding interactions simultaneously further demonstrates how this approach could expand the fluorescent toolbox currently used to detect and image proteins.

A new approach for direct imaging of Alpha radiation by using Micro Pattern Gas Detectors in SQS mode

NASA Astrophysics Data System (ADS)

Souri, R.; Negarestani, A.; Mahani, M.

2018-03-01

In this study, the design, simulation and construction of three micro pattern gas-detectors, THGEM, with different geometric dimensions are presented. Moreover, their ability of operation in SQS mode to determine the incident rays position without using any conventional imaging system is investigated. In the presence of UV absorbing gas mixtures, the proportional mode of the gas detector operation is followed by SQS mode as soon as the visible light column appears at the ray entrance location. In the method employed, each THGEM hole as an image pixel independent of other holes can operate in SQS mode with emerging a light column. As a consequence, it can be used for alpha beam imaging since the brightness of each hole at a certain voltage is proportional to the number of primary electrons entering the hole.

Protein recognition by a pattern-generating fluorescent molecular probe

NASA Astrophysics Data System (ADS)

Pode, Zohar; Peri-Naor, Ronny; Georgeson, Joseph M.; Ilani, Tal; Kiss, Vladimir; Unger, Tamar; Markus, Barak; Barr, Haim M.; Motiei, Leila; Margulies, David

2017-12-01

Fluorescent molecular probes have become valuable tools in protein research; however, the current methods for using these probes are less suitable for analysing specific populations of proteins in their native environment. In this study, we address this gap by developing a unimolecular fluorescent probe that combines the properties of small-molecule-based probes and cross-reactive sensor arrays (the so-called chemical 'noses/tongues'). On the one hand, the probe can detect different proteins by generating unique identification (ID) patterns, akin to cross-reactive arrays. On the other hand, its unimolecular scaffold and selective binding enable this ID-generating probe to identify combinations of specific protein families within complex mixtures and to discriminate among isoforms in living cells, where macroscopic arrays cannot access. The ability to recycle the molecular device and use it to track several binding interactions simultaneously further demonstrates how this approach could expand the fluorescent toolbox currently used to detect and image proteins.

Approaches to developing alternative and predictive toxicology based on PBPK/PD and QSAR modeling.

PubMed Central

Yang, R S; Thomas, R S; Gustafson, D L; Campain, J; Benjamin, S A; Verhaar, H J; Mumtaz, M M

1998-01-01

Systematic toxicity testing, using conventional toxicology methodologies, of single chemicals and chemical mixtures is highly impractical because of the immense numbers of chemicals and chemical mixtures involved and the limited scientific resources. Therefore, the development of unconventional, efficient, and predictive toxicology methods is imperative. Using carcinogenicity as an end point, we present approaches for developing predictive tools for toxicologic evaluation of chemicals and chemical mixtures relevant to environmental contamination. Central to the approaches presented is the integration of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) and quantitative structure--activity relationship (QSAR) modeling with focused mechanistically based experimental toxicology. In this development, molecular and cellular biomarkers critical to the carcinogenesis process are evaluated quantitatively between different chemicals and/or chemical mixtures. Examples presented include the integration of PBPK/PD and QSAR modeling with a time-course medium-term liver foci assay, molecular biology and cell proliferation studies. Fourier transform infrared spectroscopic analyses of DNA changes, and cancer modeling to assess and attempt to predict the carcinogenicity of the series of 12 chlorobenzene isomers. Also presented is an ongoing effort to develop and apply a similar approach to chemical mixtures using in vitro cell culture (Syrian hamster embryo cell transformation assay and human keratinocytes) methodologies and in vivo studies. The promise and pitfalls of these developments are elaborated. When successfully applied, these approaches may greatly reduce animal usage, personnel, resources, and time required to evaluate the carcinogenicity of chemicals and chemical mixtures. Images Figure 6 PMID:9860897

The comparative clinical study of efficacy of Gamisoyo-San (Jiaweixiaoyaosan) on generalized anxiety disorder according to differently manufactured preparations: multicenter, randomized, double blind, placebo controlled trial.

PubMed

Park, Dae-Myung; Kim, Seok-Hwan; Park, Yang-Chun; Kang, Wee-Chang; Lee, Sang-Ryong; Jung, In-Chul

2014-12-02

Gamisoyo-San (GSS) is a well-known Traditional Korean Medicine shown to be effective on mood disorders. The purpose of this research is to examine the effect of Gamisoyo-San on generalized anxiety disorder by its differently manufactured preparations. Multicenter, randomized, double-blinded, placebo-controlled study was set for 147 patients with generalized anxiety disorder recruited from November 1st 2009 to December 16th 2010. They were given Gamisoyo-San individual extract mixture (extraction done for each crude materia medica separately) or Gamisoyo-San multi-compound extract (extraction done for whole materia medica at once) or controlled medication. Hamilton Rating Scale for Anxiety (HAM-A), Korean State-Trait Anxiety Inventory (K-STAI), Penn State Worry Questionnaire (PSWQ), Korean Beck Depression Inventroy (K-BDI), Symptom Checklist-90-Revised (SCL-90-R), and Korean WHO Quality of Life Scale Abbreviated Version (WHOQOL-BREF) were evaluated. We also applied Pattern Identification tool for 'JingJi and ZhengChong (, Traditional Korean Medicine term which correlates with generalized anxiety disorder)' to patients to evaluate different responses among 9 patterns. HAM-A scores of Gamisoyo-San multi-compound extract group showed greater decrease compared to Gamisoyo-San individual extract mixture group and placebo group, but the difference was insignificant. WHOQOL-BREF scores of Gamisoyo-San multi-compound extract group showed significant increase compared to Gamisoyo-San individual extract mixture group and placebo group. In Heart blood deficiency pattern, the Gamisoyo-San multi-compound extract group showed significant decrease in K-BDI compared to the Gamisoyo-San individual extract mixture group. Gamisoyo-San did not improve anxiety level of GAD patients. However, it can be useful to improve quality of life, and reduce depressive, obsessive-compulsive, somatic symptoms of generalized anxiety disorder. Gamisoyo-San multi-compound seemed more effective than Gamisoyo-San individual extract mixture, especially in Heart blood deficiency pattern. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Evaluation of DNA mixtures from database search.

PubMed

Chung, Yuk-Ka; Hu, Yue-Qing; Fung, Wing K

2010-03-01

With the aim of bridging the gap between DNA mixture analysis and DNA database search, a novel approach is proposed to evaluate the forensic evidence of DNA mixtures when the suspect is identified by the search of a database of DNA profiles. General formulae are developed for the calculation of the likelihood ratio for a two-person mixture under general situations including multiple matches and imperfect evidence. The influence of the prior probabilities on the weight of evidence under the scenario of multiple matches is demonstrated by a numerical example based on Hong Kong data. Our approach is shown to be capable of presenting the forensic evidence of DNA mixtures in a comprehensive way when the suspect is identified through database search.

A modeling approach to account for toxicokinetic interactions in the calculation of biological hazard index for chemical mixtures.

PubMed

Haddad, S; Tardif, R; Viau, C; Krishnan, K

1999-09-05

Biological hazard index (BHI) is defined as biological level tolerable for exposure to mixture, and is calculated by an equation similar to the conventional hazard index. The BHI calculation, at the present time, is advocated for use in situations where toxicokinetic interactions do not occur among mixture constituents. The objective of this study was to develop an approach for calculating interactions-based BHI for chemical mixtures. The approach consisted of simulating the concentration of exposure indicator in the biological matrix of choice (e.g. venous blood) for each component of the mixture to which workers are exposed and then comparing these to the established BEI values, for calculating the BHI. The simulation of biomarker concentrations was performed using a physiologically-based toxicokinetic (PBTK) model which accounted for the mechanism of interactions among all mixture components (e.g. competitive inhibition). The usefulness of the present approach is illustrated by calculating BHI for varying ambient concentrations of a mixture of three chemicals (toluene (5-40 ppm), m-xylene (10-50 ppm), and ethylbenzene (10-50 ppm)). The results show that the interactions-based BHI can be greater or smaller than that calculated on the basis of additivity principle, particularly at high exposure concentrations. At lower exposure concentrations (e.g. 20 ppm each of toluene, m-xylene and ethylbenzene), the BHI values obtained using the conventional methodology are similar to the interactions-based methodology, confirming that the consequences of competitive inhibition are negligible at lower concentrations. The advantage of the PBTK model-based methodology developed in this study relates to the fact that, the concentrations of individual chemicals in mixtures that will not result in a significant increase in the BHI (i.e. > 1) can be determined by iterative simulation.

Bayesian decision and mixture models for AE monitoring of steel-concrete composite shear walls

NASA Astrophysics Data System (ADS)

Farhidzadeh, Alireza; Epackachi, Siamak; Salamone, Salvatore; Whittaker, Andrew S.

2015-11-01

This paper presents an approach based on an acoustic emission technique for the health monitoring of steel-concrete (SC) composite shear walls. SC composite walls consist of plain (unreinforced) concrete sandwiched between steel faceplates. Although the use of SC system construction has been studied extensively for nearly 20 years, little-to-no attention has been devoted to the development of structural health monitoring techniques for the inspection of damage of the concrete behind the steel plates. In this work an unsupervised pattern recognition algorithm based on probability theory is proposed to assess the soundness of the concrete infill, and eventually provide a diagnosis of the SC wall’s health. The approach is validated through an experimental study on a large-scale SC shear wall subjected to a displacement controlled reversed cyclic loading.

A FLEXIBLE APPROACH FOR EVALUATING FIXED RATIO MIXTURES OF FULL AND PARTIAL AGONISTS FOR MIXTURES OF MANY CHEMICALS.

EPA Science Inventory

Detecting interaction in chemical mixtures can be complicated by differences in the shapes of the dose-response curves of the individual components (e.g. mixtures of full and partial agonists with differing response maxima). We present an analysis scheme where flexible single che...

Maximum workplace concentration values and carcinogenicity classification for mixtures.

PubMed Central

Bartsch, R; Forderkunz, S; Reuter, U; Sterzl-Eckert, H; Greim, H

1998-01-01

In Germany, the Commission for the Investigation of Health Hazards of Chemical Compounds in the Work Area (MAK Commission) generally sets maximum workplace concentration values (i.e., a proposed occupational exposure level [OEL]) for single substances, not for mixtures. For mixtures containing substances with a genotoxic and carcinogenic potential, the commission considered it scientifically inappropriate to establish a safe threshold. This approach is currently under discussion. Carcinogenic mixtures are categorized according to either the carcinogenicity of the mixture or the classification of the carcinogenic substances included. In regulating exposure to mixtures, an approach similar to that used by the American Conference of Governmental Hygienists is proposed: For components with the same target organ and mode of action or interfering metabolism, synergistic effects must be expected and the respective OELs must be lowered. However, if there is proof that the components act independently, the OELs of the individual compounds are not considered to be modified. In the view of the commission, calculating OELs for solvent mixtures according to their liquid phase composition is not justified, and the setting of scientifically based OELs for complex mixtures is not possible. PMID:9860883

Detecting Math Anxiety with a Mixture Partial Credit Model

ERIC Educational Resources Information Center

Ölmez, Ibrahim Burak; Cohen, Allan S.

2017-01-01

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

Brief Report: A Growth Mixture Model of Occupational Aspirations of Individuals with High-Incidence Disabilities

ERIC Educational Resources Information Center

Lee, In Heok; Rojewski, Jay W.

2013-01-01

A previous longitudinal study of the occupational aspirations of individuals with high-incidence disabilities revealed multiple longitudinal patterns for individuals with learning disabilities or emotional-behavioral disorders. Growth mixture modeling was used to determine whether individuals in these two high-incidence disabilities groups (N =…

A mixture approach to the acoustic properties of a macroscopically inhomogeneous porous aluminum in the equivalent fluid approximation.

PubMed

Sacristan, C J; Dupont, T; Sicot, O; Leclaire, P; Verdière, K; Panneton, R; Gong, X L

2016-10-01

The acoustic properties of an air-saturated macroscopically inhomogeneous aluminum foam in the equivalent fluid approximation are studied. A reference sample built by forcing a highly compressible melamine foam with conical shape inside a constant diameter rigid tube is studied first. In this process, a radial compression varying with depth is applied. With the help of an assumption on the compressed pore geometry, properties of the reference sample can be modelled everywhere in the thickness and it is possible to use the classical transfer matrix method as theoretical reference. In the mixture approach, the material is viewed as a mixture of two known materials placed in a patchwork configuration and with proportions of each varying with depth. The properties are derived from the use of a mixing law. For the reference sample, the classical transfer matrix method is used to validate the experimental results. These results are used to validate the mixture approach. The mixture approach is then used to characterize a porous aluminium for which only the properties of the external faces are known. A porosity profile is needed and is obtained from the simulated annealing optimization process.

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.

Use of the Maximum Cumulative Ratio As an Approach for Prioritizing Aquatic Coexposure to Plant Protection Products: A Case Study of a Large Surface Water Monitoring Database.

PubMed

Vallotton, Nathalie; Price, Paul S

2016-05-17

This paper uses the maximum cumulative ratio (MCR) as part of a tiered approach to evaluate and prioritize the risk of acute ecological effects from combined exposures to the plant protection products (PPPs) measured in 3 099 surface water samples taken from across the United States. Assessments of the reported mixtures performed on a substance-by-substance approach and using a Tier One cumulative assessment based on the lowest acute ecotoxicity benchmark gave the same findings for 92.3% of the mixtures. These mixtures either did not indicate a potential risk for acute effects or included one or more individual PPPs that had concentrations in excess of their benchmarks. A Tier Two assessment using a trophic level approach was applied to evaluate the remaining 7.7% of the mixtures. This assessment reduced the number of mixtures of concern by eliminating the combination of endpoint from multiple trophic levels, identified invertebrates and nonvascular plants as the most susceptible nontarget organisms, and indicated that a only a very limited number of PPPs drove the potential concerns. The combination of the measures of cumulative risk and the MCR enabled the identification of a small subset of mixtures where a potential risk would be missed in substance-by-substance assessments.

Prediction of toxicity of zinc and nickel mixtures to Artemia sp. at various salinities: From additivity to antagonism.

PubMed

Damasceno, Évila Pinheiro; de Figuerêdo, Lívia Pitombeira; Pimentel, Marcionília Fernandes; Loureiro, Susana; Costa-Lotufo, Letícia Veras

2017-08-01

Few studies have examined the toxicity of metal mixtures to marine organisms exposed to different salinities. The aim of the present study was to investigate the acute toxicity of zinc and nickel exposures singly and in combination to Artemia sp. under salinities of 10, 17, and 35 psu. The mixture concentrations were determined according to individual toxic units (TUs) to follow a fixed ratio design. Zinc was more toxic than nickel, and both their individual toxicities were higher at lower salinities. These changes in toxicity can be attributed to the Biotic Ligand Model (BLM) rather than to metal speciation. To analyze the mixture effect, the observed data were compared with the expected mixture effects predicted by the concentration addition (CA) model and by deviations for synergistic/antagonistic interactions and dose-level and dose-ratio dependencies. For a salinity of 35 psu, the mixture had no deviations; therefore, the effects were additive. After decreasing the salinity to 17 psu, the toxicity pattern changed to antagonism at low concentrations and synergism at higher equivalent LC 50 levels. For the lowest salinity tested (10 psu), antagonism was observed. The speciations of both metals were similar when in a mixture and when isolated, and changes in toxicity patterns are more related to the organism's physiology than metal speciation. Therefore, besides considering chemical interactions in real-world scenarios, where several chemicals can be present, the influence of abiotic factors, such as salinity, should also be considered. Copyright © 2017 Elsevier Inc. All rights reserved.

Laser Printing of Superhydrophobic Patterns from Mixtures of Hydrophobic Silica Nanoparticles and Toner Powder.

PubMed

Ngo, Chi-Vinh; Chun, Doo-Man

2016-11-08

In this work, a new and facile dry printing method was developed for the direct fabrication of superhydrophobic patterns based on silica nanoparticles. Mixtures of hydrophobic fumed silica nanoparticles and toner powder were printed on paper and polymer sheets using a commercial laser printer to produce the superhydrophobic patterns. The mixing ratio of the toner powder (for the laser printer) to hydrophobic silica was also investigated to optimize both the printing quality and the superhydrophobicity of the printed areas. The proper mixing ratio was then used to print various superhydrophobic patterns, including triangular, square, circular, and complex arrangements, to demonstrate that superhydrophobic surfaces with different patterns can be fabricated in a few seconds without any post-processing. The superhydrophobicity of each sample was evaluated by contact angle measurements, and all printed areas showed contact angles greater than 150°. The research described here opens the possibility of rapid production of superhydrophobic surfaces with various patterns. Ultimately, the obtained findings may have a significant impact on applications related to self-cleaning, control of water geometry and position, fluid mixing and fluid transport.

Laser Printing of Superhydrophobic Patterns from Mixtures of Hydrophobic Silica Nanoparticles and Toner Powder

PubMed Central

Ngo, Chi-Vinh; Chun, Doo-Man

2016-01-01

In this work, a new and facile dry printing method was developed for the direct fabrication of superhydrophobic patterns based on silica nanoparticles. Mixtures of hydrophobic fumed silica nanoparticles and toner powder were printed on paper and polymer sheets using a commercial laser printer to produce the superhydrophobic patterns. The mixing ratio of the toner powder (for the laser printer) to hydrophobic silica was also investigated to optimize both the printing quality and the superhydrophobicity of the printed areas. The proper mixing ratio was then used to print various superhydrophobic patterns, including triangular, square, circular, and complex arrangements, to demonstrate that superhydrophobic surfaces with different patterns can be fabricated in a few seconds without any post-processing. The superhydrophobicity of each sample was evaluated by contact angle measurements, and all printed areas showed contact angles greater than 150°. The research described here opens the possibility of rapid production of superhydrophobic surfaces with various patterns. Ultimately, the obtained findings may have a significant impact on applications related to self-cleaning, control of water geometry and position, fluid mixing and fluid transport. PMID:27824132

Modulation of Spatiotemporal Particle Patterning in Evaporating Droplets: Applications to Diagnostics and Materials Science.

PubMed

Guha, Rajarshi; Mohajerani, Farzad; Mukhopadhyay, Ahana; Collins, Matthew D; Sen, Ayusman; Velegol, Darrell

2017-12-13

Spatiotemporal particle patterning in evaporating droplets lacks a common design framework. Here, we demonstrate autonomous control of particle distribution in evaporating droplets through the imposition of a salt-induced self-generated electric field as a generalized patterning strategy. Through modeling, a new dimensionless number, termed "capillary-phoresis" (CP) number, arises, which determines the relative contributions of electrokinetic and convective transport to pattern formation, enabling one to accurately predict the mode of particle assembly by controlling the spontaneous electric field and surface potentials. Modulation of the CP number allows the particles to be focused in a specific region in space or distributed evenly. Moreover, starting with a mixture of two different particle types, their relative placement in the ensuing pattern can be controlled, allowing coassemblies of multiple, distinct particle populations. By this approach, hypermethylated DNA, prevalent in cancerous cells, can be qualitatively distinguished from normal DNA of comparable molecular weights. In other examples, we show uniform dispersion of several particle types (polymeric colloids, multiwalled carbon nanotubes, and molecular dyes) on different substrates (metallic Cu, metal oxide, and flexible polymer), as dictated by the CP number. Depending on the particle, the highly uniform distribution leads to surfaces with a lower sheet resistance, as well as superior dye-printed displays.

Hierarchical Analytical Approaches for Unraveling the Composition of Proprietary Mixtures

EPA Pesticide Factsheets

The composition of commercial mixtures including pesticide inert ingredients, aircraft deicers, and aqueous film-forming foam (AFFF) formulations, and by analogy, fracking fluids, are proprietary. Quantitative analytical methodologies can only be developed for mixture components once their identities are known. Because proprietary mixtures may contain volatile and non-volatile components, a hierarchy of analytical methods is often required for the full identification of all proprietary mixture components.

Benchmarking Water Quality from Wastewater to Drinking Waters Using Reduced Transcriptome of Human Cells.

PubMed

Xia, Pu; Zhang, Xiaowei; Zhang, Hanxin; Wang, Pingping; Tian, Mingming; Yu, Hongxia

2017-08-15

One of the major challenges in environmental science is monitoring and assessing the risk of complex environmental mixtures. In vitro bioassays with limited key toxicological end points have been shown to be suitable to evaluate mixtures of organic pollutants in wastewater and recycled water. Omics approaches such as transcriptomics can monitor biological effects at the genome scale. However, few studies have applied omics approach in the assessment of mixtures of organic micropollutants. Here, an omics approach was developed for profiling bioactivity of 10 water samples ranging from wastewater to drinking water in human cells by a reduced human transcriptome (RHT) approach and dose-response modeling. Transcriptional expression of 1200 selected genes were measured by an Ampliseq technology in two cell lines, HepG2 and MCF7, that were exposed to eight serial dilutions of each sample. Concentration-effect models were used to identify differentially expressed genes (DEGs) and to calculate effect concentrations (ECs) of DEGs, which could be ranked to investigate low dose response. Furthermore, molecular pathways disrupted by different samples were evaluated by Gene Ontology (GO) enrichment analysis. The ability of RHT for representing bioactivity utilizing both HepG2 and MCF7 was shown to be comparable to the results of previous in vitro bioassays. Finally, the relative potencies of the mixtures indicated by RHT analysis were consistent with the chemical profiles of the samples. RHT analysis with human cells provides an efficient and cost-effective approach to benchmarking mixture of micropollutants and may offer novel insight into the assessment of mixture toxicity in water.

More than child's play: variable- and pattern-centered approaches for examining effects of sports participation on youth development.

PubMed

Zarrett, Nicole; Fay, Kristen; Li, Yibing; Carrano, Jennifer; Phelps, Erin; Lerner, Richard M

2009-03-01

The authors used data from Grades 5 through 7 of the longitudinal 4-H Study of Positive Youth Development to assess relations among sports participation, other out-of-school-time (OST) activities, and indicators of youth development. They used a mixture of variable- and pattern-centered analyses aimed at disentangling different features of participation (i.e., intensity, breadth). The benefits of sports participation were found to depend, in part, on specific combinations of multiple activities in which youths participated along with sports. In particular, participation in a combination of sports and youth development programs was related to positive youth development and youth contribution, even after controlling for the total time youths spent in OST activities and their sports participation duration. Adolescents' total time spent participating in OST activities, duration of participation in sports, and activity participation pattern each explained a unique part of the variance in some of the indicators of youth functioning. These findings suggest the need for future research to simultaneously assess multiple indices of OST activity participation.

Conceptual recurrence plots: revealing patterns in human discourse.

PubMed

Angus, Daniel; Smith, Andrew; Wiles, Janet

2012-06-01

Human discourse contains a rich mixture of conceptual information. Visualization of the global and local patterns within this data stream is a complex and challenging problem. Recurrence plots are an information visualization technique that can reveal trends and features in complex time series data. The recurrence plot technique works by measuring the similarity of points in a time series to all other points in the same time series and plotting the results in two dimensions. Previous studies have applied recurrence plotting techniques to textual data; however, these approaches plot recurrence using term-based similarity rather than conceptual similarity of the text. We introduce conceptual recurrence plots, which use a model of language to measure similarity between pairs of text utterances, and the similarity of all utterances is measured and displayed. In this paper, we explore how the descriptive power of the recurrence plotting technique can be used to discover patterns of interaction across a series of conversation transcripts. The results suggest that the conceptual recurrence plotting technique is a useful tool for exploring the structure of human discourse.

Identification of natural metabolites in mixture: a pattern recognition strategy based on (13)C NMR.

PubMed

Hubert, Jane; Nuzillard, Jean-Marc; Purson, Sylvain; Hamzaoui, Mahmoud; Borie, Nicolas; Reynaud, Romain; Renault, Jean-Hugues

2014-03-18

Because of their highly complex metabolite profile, the chemical characterization of bioactive natural extracts usually requires time-consuming multistep purification procedures to achieve the structural elucidation of pure individual metabolites. The aim of the present work was to develop a dereplication strategy for the identification of natural metabolites directly within mixtures. Exploiting the polarity range of metabolites, the principle was to rapidly fractionate a multigram quantity of a crude extract by centrifugal partition extraction (CPE). The obtained fractions of simplified chemical composition were subsequently analyzed by (13)C NMR. After automatic collection and alignment of (13)C signals across spectra, hierarchical clustering analysis (HCA) was performed for pattern recognition. As a result, strong correlations between (13)C signals of a single structure within the mixtures of the fraction series were visualized as chemical shift clusters. Each cluster was finally assigned to a molecular structure with the help of a locally built (13)C NMR chemical shift database. The proof of principle of this strategy was achieved on a simple model mixture of commercially available plant secondary metabolites and then applied to a bark extract of the African tree Anogeissus leiocarpus Guill. & Perr. (Combretaceae). Starting from 5 g of this genuine extract, the fraction series was generated by CPE in only 95 min. (13)C NMR analyses of all fractions followed by pattern recognition of (13)C chemical shifts resulted in the unambiguous identification of seven major compounds, namely, sericoside, trachelosperogenin E, ellagic acid, an epimer mixture of (+)-gallocatechin and (-)-epigallocatechin, 3,3'-di-O-methylellagic acid 4'-O-xylopyranoside, and 3,4,3'-tri-O-methylflavellagic acid 4'-O-glucopyranoside.

Conceptual model for assessing criteria air pollutants in a multipollutant context: A modified adverse outcome pathway approach.

PubMed

Buckley, Barbara; Farraj, Aimen

2015-09-01

Air pollution consists of a complex mixture of particulate and gaseous components. Individual criteria and other hazardous air pollutants have been linked to adverse respiratory and cardiovascular health outcomes. However, assessing risk of air pollutant mixtures is difficult since components are present in different combinations and concentrations in ambient air. Recent mechanistic studies have limited utility because of the inability to link measured changes to adverse outcomes that are relevant to risk assessment. New approaches are needed to address this challenge. The purpose of this manuscript is to describe a conceptual model, based on the adverse outcome pathway approach, which connects initiating events at the cellular and molecular level to population-wide impacts. This may facilitate hazard assessment of air pollution mixtures. In the case reports presented here, airway hyperresponsiveness and endothelial dysfunction are measurable endpoints that serve to integrate the effects of individual criteria air pollutants found in inhaled mixtures. This approach incorporates information from experimental and observational studies into a sequential series of higher order effects. The proposed model has the potential to facilitate multipollutant risk assessment by providing a framework that can be used to converge the effects of air pollutants in light of common underlying mechanisms. This approach may provide a ready-to-use tool to facilitate evaluation of health effects resulting from exposure to air pollution mixtures. Published by Elsevier Ireland Ltd.

Current Evidence on the Association of Dietary Patterns and Bone Health: A Scoping Review123

PubMed Central

Movassagh, Elham Z

2017-01-01

Nutrition is an important modifiable factor that affects bone health. Diet is a complex mixture of nutrients and foods that correlate or interact with each other. Dietary pattern approaches take into account contributions from various aspects of diet. Findings from dietary pattern studies could complement those from single-nutrient and food studies on bone health. In this study we aimed to conduct a scoping review of the literature that assessed the impact of dietary patterns (derived with the use of both a priori and data-driven approaches) on bone outcomes, including bone mineral status, bone biomarkers, osteoporosis, and fracture risk. We retrieved 49 human studies up to June 2016 from the PubMed, Embase, and CINAHL databases. Most of these studies used a data-driven method, especially factor analysis, to derive dietary patterns. Several studies examined adherence to a variety of the a priori dietary indexes, including the Mediterranean diet score, the Healthy Eating Index (HEI), and the Alternative Healthy Eating Index (AHEI). The bone mineral density (BMD) diet score was developed to measure adherence to a dietary pattern beneficial to bone mineral density. Findings revealed a beneficial impact of higher adherence to a “healthy” dietary pattern derived using a data-driven method, the Mediterranean diet, HEI, AHEI, Dietary Diversity Score, Diet Quality Index–International, BMD Diet Score, Healthy Diet Indicator, and Korean Diet Score, on bone. In contrast, the “Western” dietary pattern and those featuring some aspects of an unhealthy diet were associated inversely with bone health. In both a priori and data-driven dietary pattern studies, a dietary pattern that emphasized the intake of fruit, vegetables, whole grains, poultry and fish, nuts and legumes, and low-fat dairy products and de-emphasized the intake of soft drinks, fried foods, meat and processed products, sweets and desserts, and refined grains showed a beneficial impact on bone health. Overall, adherence to a healthy dietary pattern consisting of the above-mentioned food groups can improve bone mineral status and decrease osteoporosis and fracture risk. PMID:28096123

Automated visual inspection for polished stone manufacture

NASA Astrophysics Data System (ADS)

Smith, Melvyn L.; Smith, Lyndon N.

2003-05-01

Increased globalisation of the ornamental stone market has lead to increased competition and more rigorous product quality requirements. As such, there are strong motivators to introduce new, more effective, inspection technologies that will help enable stone processors to reduce costs, improve quality and improve productivity. Natural stone surfaces may contain a mixture of complex two-dimensional (2D) patterns and three-dimensional (3D) features. The challenge in terms of automated inspection is to develop systems able to reliably identify 3D topographic defects, either naturally occurring or resulting from polishing, in the presence of concomitant complex 2D stochastic colour patterns. The resulting real-time analysis of the defects may be used in adaptive process control, in order to avoid the wasteful production of defective product. An innovative approach, using structured light and based upon an adaptation of the photometric stereo method, has been pioneered and developed at UWE to isolate and characterize mixed 2D and 3D surface features. The method is able to undertake tasks considered beyond the capabilities of existing surface inspection techniques. The approach has been successfully applied to real stone samples, and a selection of experimental results is presented.

Patterns of Weight Change in Black Americans: Pooled Analysis from Three Behavioral Weight Loss Trials

PubMed Central

Morales, Knashawn H.; Kumanyika, Shiriki K.; Fassbender, Jennifer E.; Good, Jerene; Localio, A. Russell; Wadden, Thomas A.

2014-01-01

Objective Differentiating trajectories of weight change and identifying associated baseline predictors can provide insights for improving behavioral obesity treatment outcomes. Design and Methods Secondary, observational analyses using growth mixture models were conducted in pooled data for 604 black American, primarily female adults in three completed clinical trials. Covariates of identified patterns were evaluated. Results The best fitting model identified three patterns over 2 years: 1) mean weight loss of approximately 2 kg (n=519); 2) mean weight loss of approximately 3 kg at 1 year, followed by ~ 4 kg regain (n=61); and 3) mean weight loss of approximately 20 kg at 1 year followed by ~ 4 kg regain (n=24, with 23 from one study). In final multivariate analyses, higher BMI predicted having pattern 2 (OR[95% CI]) 1.10[1.03, 1.17]) or 3 (OR[95% CI] 1.42[1.25, 1.63]), and higher dietary fat score was predictive of a lower odds of having patterns 2 (OR[95% CI] 0.37[0.15, 0.94]) or 3 (OR[95% CI] 0.23[0.07, 0.79]). Conclusions Findings were consistent with moderate, clinically non-significant weight loss as the predominant pattern across all studies. Results underscore the need to develop novel and more carefully targeted and tailored approaches to facilitating weight loss in black American adults. PMID:25251464

Formation mechanism of complex pattern on fishes' skin

NASA Astrophysics Data System (ADS)

Li, Xia; Liu, Shuhua

2009-10-01

In this paper, the formation mechanism of the complex patterns observed on the skin of fishes has been investigated by a two-coupled reaction diffusion model. The effects of coupling strength between two layers play an important role in the pattern-forming process. It is found that only the epidermis layer can produce complicated patterns that have structures on more than one length scale. These complicated patterns including super-stripe pattern, mixture of spots and stripe, and white-eye pattern are similar to the pigmentation patterns on fishes' skin.

Investigating Factorial Invariance of Latent Variables Across Populations When Manifest Variables Are Missing Completely

PubMed Central

Widaman, Keith F.; Grimm, Kevin J.; Early, Dawnté R.; Robins, Richard W.; Conger, Rand D.

2013-01-01

Difficulties arise in multiple-group evaluations of factorial invariance if particular manifest variables are missing completely in certain groups. Ad hoc analytic alternatives can be used in such situations (e.g., deleting manifest variables), but some common approaches, such as multiple imputation, are not viable. At least 3 solutions to this problem are viable: analyzing differing sets of variables across groups, using pattern mixture approaches, and a new method using random number generation. The latter solution, proposed in this article, is to generate pseudo-random normal deviates for all observations for manifest variables that are missing completely in a given sample and then to specify multiple-group models in a way that respects the random nature of these values. An empirical example is presented in detail comparing the 3 approaches. The proposed solution can enable quantitative comparisons at the latent variable level between groups using programs that require the same number of manifest variables in each group. PMID:24019738

Isoform-level gene expression patterns in single-cell RNA-sequencing data.

PubMed

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Pawitan, Yudi; Rantalainen, Mattias

2018-02-27

RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data. We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16,562 isoform-pairs from 4,929 genes. Among those, 26% of the discovered patterns were significant (p<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. The effect of drop-out events, mean expression level, and properties of the expression distribution on the performances of ISOP were also investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoformlevel preference, commitment and heterogeneity in single-cell RNA-sequencing data. The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license. mattias.rantalainen@ki.se. Supplementary data are available at Bioinformatics online.

A Mixture Rasch Model with a Covariate: A Simulation Study via Bayesian Markov Chain Monte Carlo Estimation

ERIC Educational Resources Information Center

Dai, Yunyun

2013-01-01

Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying…

Use of Non-Apical Assay Data in an Integrated Approach to Testing and Assessment of Chemical Mixtures in the Environment: the Advent of Adverse Outcome Pathway Footprinting

EPA Science Inventory

This speaker abstract is part of a session proposal for the 2018 Society of Toxicology annual meeting. I am proposing to speak about the use of new approach methods and data, such as AOPs, in mixtures risk assessment. I have developed an innovative approach called AOP footprint...

The potential of three different PCR-related approaches for the authentication of mixtures of herbal substances and finished herbal medicinal products.

PubMed

Doganay-Knapp, Kirsten; Orland, Annika; König, Gabriele M; Knöss, Werner

2018-04-01

Herbal substances and preparations thereof play an important role in healthcare systems worldwide. Due to the variety of these products regarding origin, composition and processing procedures, appropriate methodologies for quality assessment need to be considered. A majority of herbal substances is administered as multicomponent mixtures, especially in the field of Traditional Chinese Medicine and ayurvedic medicine, but also in finished medicinal products. Quality assessment of complex mixtures of herbal substances with conventional methods is challenging. Thus, emphasis of the present work was directed on the development of complementary methods to elucidate the composition of mixtures of herbal substances and finished herbal medicinal products. An indispensable prerequisite for the safe and effective use of herbal medicines is the unequivocal authentication of the medicinal plants used therein. In this context, we investigated the potential of three different PCR-related methods in the characterization and authentication of herbal substances. A multiplex PCR assay and a quantitative PCR (qPCR) assay were established to analyze defined mixtures of the herbal substances Quercus cortex, Juglandis folium, Aristolochiae herba, Matricariae flos and Salviae miltiorrhizae radix et rhizoma and a finished herbal medicinal product. Furthermore, a standard cloning approach using universal primers targeting the ITS region was established in order to allow the investigation of herbal mixtures with unknown content. The cloning approach had some limitations regarding the detection/recovery of the components in defined mixtures of herbal substances, but the complementary use of two sets of universal primer pairs increased the detection of components out of the mixture. While the multiplex PCR did not retrace all components in the defined mixtures of herbal substances, the established qPCR resulted in simultaneous and specific detection of the five target sequences in all defined mixtures. These data indicate that for authentication purposes, complementary PCR-related methods are highly recommendable for the analysis of herbal mixtures in parallel. Copyright © 2018 Elsevier GmbH. All rights reserved.

Estimating the impact of grouping misclassification on risk prediction when using the relative potency factors method to assess mixtures risk

EPA Science Inventory

Environmental health risk assessments of chemical mixtures that rely on component approaches often begin by grouping the chemicals of concern according to toxicological similarity. Approaches that assume dose addition typically are used for groups of similarly-acting chemicals an...

Risk assessments for mixtures: technical methods commonly used in the United States

EPA Science Inventory

A brief (20 minute) talk on the technical approaches used by EPA and other US agencies to assess risks posed by combined exposures to one or more chemicals. The talk systemically reviews the methodologies (whole-mixtures and component-based approaches) that are or have been used ...

Considerations for Developing a Dosimetry-Based Cumulative Risk Assessment Approach for Mixtures of Environmental Contaminants (Final Report)

EPA Science Inventory

EPA announced the availability of the final report, Considerations for Developing a Dosimetry-Based Cumulative Risk Assessment Approach for Mixtures of Environmental Contaminants. This report describes a process that can be used to determine the potential value of develop...

The determination of viscosity at liquid mixtures - Comparison of approaches

NASA Astrophysics Data System (ADS)

Michal, Schmirler; Hana, Netřebská; Jan, Kolínský

2017-09-01

The research of flow field parameters for non-stationary flow of non-Newtonian fluids carried out at the Institute of Fluid Mechanics and Thermodynamics of CTU showed the need for knowledge of determination of the resulting viscosity of a mixture of several liquids. There are several sources for determining viscosity of mixtures. It is possible either to find theoretical relations in the literature or use technical tables based on experimentally measured data. This article focuses on comparing these approaches with an experiment. The experiment was performed by a Rheotest RN 4.1 rotating viscometer produced by the company RHEOTEST Medingen. The research was carried out using a solution of glycerol and water. The research has shown great differences in results in different approaches for determining the viscosity of the liquid mixtures. The result of this paper is to determine the method of viscosity calculation that is closest to the experimental data.

Mixture class recovery in GMM under varying degrees of class separation: frequentist versus Bayesian estimation.

PubMed

Depaoli, Sarah

2013-06-01

Growth mixture modeling (GMM) represents a technique that is designed to capture change over time for unobserved subgroups (or latent classes) that exhibit qualitatively different patterns of growth. The aim of the current article was to explore the impact of latent class separation (i.e., how similar growth trajectories are across latent classes) on GMM performance. Several estimation conditions were compared: maximum likelihood via the expectation maximization (EM) algorithm and the Bayesian framework implementing diffuse priors, "accurate" informative priors, weakly informative priors, data-driven informative priors, priors reflecting partial-knowledge of parameters, and "inaccurate" (but informative) priors. The main goal was to provide insight about the optimal estimation condition under different degrees of latent class separation for GMM. Results indicated that optimal parameter recovery was obtained though the Bayesian approach using "accurate" informative priors, and partial-knowledge priors showed promise for the recovery of the growth trajectory parameters. Maximum likelihood and the remaining Bayesian estimation conditions yielded poor parameter recovery for the latent class proportions and the growth trajectories. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

A Computational Algorithm for Functional Clustering of Proteome Dynamics During Development

PubMed Central

Wang, Yaqun; Wang, Ningtao; Hao, Han; Guo, Yunqian; Zhen, Yan; Shi, Jisen; Wu, Rongling

2014-01-01

Phenotypic traits, such as seed development, are a consequence of complex biochemical interactions among genes, proteins and metabolites, but the underlying mechanisms that operate in a coordinated and sequential manner remain elusive. Here, we address this issue by developing a computational algorithm to monitor proteome changes during the course of trait development. The algorithm is built within the mixture-model framework in which each mixture component is modeled by a specific group of proteins that display a similar temporal pattern of expression in trait development. A nonparametric approach based on Legendre orthogonal polynomials was used to fit dynamic changes of protein expression, increasing the power and flexibility of protein clustering. By analyzing a dataset of proteomic dynamics during early embryogenesis of the Chinese fir, the algorithm has successfully identified several distinct types of proteins that coordinate with each other to determine seed development in this forest tree commercially and environmentally important to China. The algorithm will find its immediate applications for the characterization of mechanistic underpinnings for any other biological processes in which protein abundance plays a key role. PMID:24955031

A peptidomic approach for monitoring and characterising peptide cyanotoxins produced in Italian lakes by matrix-assisted laser desorption/ionisation and quadrupole time-of-flight mass spectrometry.

PubMed

Ferranti, Pasquale; Nasi, Antonella; Bruno, Milena; Basile, Adriana; Serpe, Luigi; Gallo, Pasquale

2011-05-15

In recent years, the occurrence of cyanobacterial blooms in eutrophic freshwaters has been described all over the world, including most European countries. Blooms of cyanobacteria may produce mixtures of toxic secondary metabolites, called cyanotoxins. Among these, the most studied are microcystins, a group of cyclic heptapeptides, because of their potent hepatotoxicity and activity as tumour promoters. Other peptide cyanotoxins have been described whose structure and toxicity have not been thoroughly studied. Herein we present a peptidomic approach aimed to characterise and quantify the peptide cyanotoxins produced in two Italian lakes, Averno and Albano. The procedure was based on matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry mass spectrometry (MALDI-TOF-MS) analysis for rapid detection and profiling of the peptide mixture complexity, combined with liquid chromatography/electrospray ionisation quadrupole time-of- flight tandem mass spectrometry (LC/ESI-Q-TOF-MS/MS) which provided unambiguous structural identification of the main compounds, as well as accurate quantitative analysis of microcystins. In the case of Lake Averno, a novel variant of microcystin-RR and two novel anabaenopeptin variants (Anabaenopeptins B(1) and Anabaenopeptin F(1)), presenting homoarginine in place of the commonly found arginine, were detected and characterised. In Lake Albano, the peculiar peptide patterns in different years were compared, as an example of the potentiality of the peptidomic approach for fast screening analysis, prior to fine structural analysis and determination of cyanotoxins, which included six novel aeruginosin variants. This approach allows for wide range monitoring of cyanobacteria blooms, and to collect data for evaluating possible health risks to consumers, through the panel of the compounds produced along different years. Copyright © 2011 John Wiley & Sons, Ltd.

Modeling sports highlights using a time-series clustering framework and model interpretation

NASA Astrophysics Data System (ADS)

Radhakrishnan, Regunathan; Otsuka, Isao; Xiong, Ziyou; Divakaran, Ajay

2005-01-01

In our past work on sports highlights extraction, we have shown the utility of detecting audience reaction using an audio classification framework. The audio classes in the framework were chosen based on intuition. In this paper, we present a systematic way of identifying the key audio classes for sports highlights extraction using a time series clustering framework. We treat the low-level audio features as a time series and model the highlight segments as "unusual" events in a background of an "usual" process. The set of audio classes to characterize the sports domain is then identified by analyzing the consistent patterns in each of the clusters output from the time series clustering framework. The distribution of features from the training data so obtained for each of the key audio classes, is parameterized by a Minimum Description Length Gaussian Mixture Model (MDL-GMM). We also interpret the meaning of each of the mixture components of the MDL-GMM for the key audio class (the "highlight" class) that is correlated with highlight moments. Our results show that the "highlight" class is a mixture of audience cheering and commentator's excited speech. Furthermore, we show that the precision-recall performance for highlights extraction based on this "highlight" class is better than that of our previous approach which uses only audience cheering as the key highlight class.

Discovery of phosphorylation motif mixtures in phosphoproteomics data

PubMed Central

Ritz, Anna; Shakhnarovich, Gregory; Salomon, Arthur R.; Raphael, Benjamin J.

2009-01-01

Motivation: Modification of proteins via phosphorylation is a primary mechanism for signal transduction in cells. Phosphorylation sites on proteins are determined in part through particular patterns, or motifs, present in the amino acid sequence. Results: We describe an algorithm that simultaneously discovers multiple motifs in a set of peptides that were phosphorylated by several different kinases. Such sets of peptides are routinely produced in proteomics experiments.Our motif-finding algorithm uses the principle of minimum description length to determine a mixture of sequence motifs that distinguish a foreground set of phosphopeptides from a background set of unphosphorylated peptides. We show that our algorithm outperforms existing motif-finding algorithms on synthetic datasets consisting of mixtures of known phosphorylation sites. We also derive a motif specificity score that quantifies whether or not the phosphoproteins containing an instance of a motif have a significant number of known interactions. Application of our motif-finding algorithm to recently published human and mouse proteomic studies recovers several known phosphorylation motifs and reveals a number of novel motifs that are enriched for interactions with a particular kinase or phosphatase. Our tools provide a new approach for uncovering the sequence specificities of uncharacterized kinases or phosphatases. Availability: Software is available at http:/cs.brown.edu/people/braphael/software.html. Contact: aritz@cs.brown.edu; braphael@cs.brown.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:18996944

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays.

PubMed

McLachlan, G J; Bean, R W; Jones, L Ben-Tovim

2006-07-01

An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

A Mathematical Model of the Olfactory Bulb for the Selective Adaptation Mechanism in the Rodent Olfactory System.

PubMed

Soh, Zu; Nishikawa, Shinya; Kurita, Yuichi; Takiguchi, Noboru; Tsuji, Toshio

2016-01-01

To predict the odor quality of an odorant mixture, the interaction between odorants must be taken into account. Previously, an experiment in which mice discriminated between odorant mixtures identified a selective adaptation mechanism in the olfactory system. This paper proposes an olfactory model for odorant mixtures that can account for selective adaptation in terms of neural activity. The proposed model uses the spatial activity pattern of the mitral layer obtained from model simulations to predict the perceptual similarity between odors. Measured glomerular activity patterns are used as input to the model. The neural interaction between mitral cells and granular cells is then simulated, and a dissimilarity index between odors is defined using the activity patterns of the mitral layer. An odor set composed of three odorants is used to test the ability of the model. Simulations are performed based on the odor discrimination experiment on mice. As a result, we observe that part of the neural activity in the glomerular layer is enhanced in the mitral layer, whereas another part is suppressed. We find that the dissimilarity index strongly correlates with the odor discrimination rate of mice: r = 0.88 (p = 0.019). We conclude that our model has the ability to predict the perceptual similarity of odorant mixtures. In addition, the model also accounts for selective adaptation via the odor discrimination rate, and the enhancement and inhibition in the mitral layer may be related to this selective adaptation.

Derivation of a reference dose for a complex petroleum hydrocarbon mixture

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

Ryer-Powder, J.E.; LaPirre, A.; Scofield, R.

1997-12-31

Petroleum hydrocarbon mixtures pose a challenge in assessing potential health effects associated with environmental exposures through impacted media. Two components of risk assessment that must be addressed when evaluating these mixtures are toxicity and environmental fate. In this paper, we focus on issues regarding toxicity. Specifically, we have developed a methodology to derive a reference dose (RfD) for a complex petroleum hydrocarbon mixture referred to as diluent. Diluent is a solvent used in the production of crude oil and is composed of hydrocarbons in the middle distillate range. Two conservative approaches to developing a reference dose for diluent are presented.more » Both involve separating the diluent into carbon number ranges (e.g., diluent consists of hydrocarbons containing between 5 carbons and greater than 21 carbons, so, the mixture can be divided into mixtures of hydrocarbons having 5 carbons, 6-11 carbons, etcetera) and assigning each range a representative RfD. In the first approach, the representative RfD for each range is that of one specific chemical within the range (e.g., the reference dose for the C{sub 5}-C{sub 8} carbon range is that of n-hexane). In the second approach, the RfD dose for each range is that of a mixture of chemicals representative of each carbon number range (e.g., the RfD for the C{sub 6} to C{sub 11} carbon range is that of mineral spirits). The RfD for each carbon range is then multiplied by the percent of diluent in the corresponding range and the products are added to arrive at a final RfD. The RfD for diluent using the first approach is estimated at 2 mg/kg-day and that using the second approach is estimated at 1 mg/kg-day.« less

Metal-Polycyclic Aromatic Hydrocarbon Mixture Toxicity in Hyalella azteca. 1. Response Surfaces and Isoboles To Measure Non-additive Mixture Toxicity and Ecological Risk.

PubMed

Gauthier, Patrick T; Norwood, Warren P; Prepas, Ellie E; Pyle, Greg G

2015-10-06

Mixtures of metals and polycyclic aromatic hydrocarbons (PAHs) occur ubiquitously in aquatic environments, yet relatively little is known regarding their potential to produce non-additive toxicity (i.e., antagonism or potentiation). A review of the lethality of metal-PAH mixtures in aquatic biota revealed that more-than-additive lethality is as common as strictly additive effects. Approaches to ecological risk assessment do not consider non-additive toxicity of metal-PAH mixtures. Forty-eight-hour water-only binary mixture toxicity experiments were conducted to determine the additive toxic nature of mixtures of Cu, Cd, V, or Ni with phenanthrene (PHE) or phenanthrenequinone (PHQ) using the aquatic amphipod Hyalella azteca. In cases where more-than-additive toxicity was observed, we calculated the possible mortality rates at Canada's environmental water quality guideline concentrations. We used a three-dimensional response surface isobole model-based approach to compare the observed co-toxicity in juvenile amphipods to predicted outcomes based on concentration addition or effects addition mixtures models. More-than-additive lethality was observed for all Cu-PHE, Cu-PHQ, and several Cd-PHE, Cd-PHQ, and Ni-PHE mixtures. Our analysis predicts Cu-PHE, Cu-PHQ, Cd-PHE, and Cd-PHQ mixtures at the Canadian Water Quality Guideline concentrations would produce 7.5%, 3.7%, 4.4% and 1.4% mortality, respectively.

Effects of binary taste stimuli on the neural activity of the hamster chorda tympani

PubMed Central

1980-01-01

Binary mixtures of taste stimuli were applied to the tongue of the hamster and the reaction of the whole corda tympani was recorded. Some of the chemicals that were paired in mixtures (HCl, NH4Cl, NaCl, CaCl2, sucrose, and D-phenylalanine) have similar tastes to human and/or hamster, and/or common stimulatory effects on individual fibers of the hamster chorda tympani; other pairs of these chemicals have dissimilar tastes and/or distinct neural stimulatory effects. The molarity of each chemical with approximately the same effect on the activity of the nerve as 0.01 M NaCl was selected, and an established relation between stimulus concentration and response allowed estimation of the effect of a "mixture" of two concentrations of one chemical. Each mixture elicited a response that was smaller than the sum of the responses to its components. However, responses to some mixtures approached this sum, and responses to other mixtures closely approached the response to a "mixture" of two concentrations of one chemical. Responses of the former variety were generated by mixtures of an electrolyte and a nonelectrolyte and the latter by mixtures of two electrolytes or two nonelectrolytes. But, beyond the distinction between electrolytes and nonelectrolytes, the whole-nerve response to a mixture could not be predicted from the known neural or psychophysical effects of its components. PMID:7411114

Differential Activity-Driven Instabilities in Biphasic Active Matter

NASA Astrophysics Data System (ADS)

Weber, Christoph A.; Rycroft, Chris H.; Mahadevan, L.

2018-06-01

Active stresses can cause instabilities in contractile gels and living tissues. Here we provide a generic hydrodynamic theory that treats these systems as a mixture of two phases of varying activity and different mechanical properties. We find that differential activity between the phases causes a uniform mixture to undergo a demixing instability. We follow the nonlinear evolution of the instability and characterize a phase diagram of the resulting patterns. Our study complements other instability mechanisms in mixtures driven by differential adhesion, differential diffusion, differential growth, and differential motion.

Spatial Analysis of “Crazy Quilts”, a Class of Potentially Random Aesthetic Artefacts

PubMed Central

Westphal-Fitch, Gesche; Fitch, W. Tecumseh

2013-01-01

Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. “Crazy quilts” represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures. PMID:24066095

Spatial analysis of "crazy quilts", a class of potentially random aesthetic artefacts.

PubMed

Westphal-Fitch, Gesche; Fitch, W Tecumseh

2013-01-01

Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. "Crazy quilts" represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures.

A novel approach for analyzing glass-transition temperature vs. composition patterns: application to pharmaceutical compound+polymer systems.

PubMed

Kalogeras, Ioannis M

2011-04-18

In medicine, polymer-based materials are commonly used as excipients of poorly water-soluble drugs. The success of the encapsulation, as well as the physicochemical stability of the products, is often reflected on their glass transition temperature (T(g)) vs. composition (w) dependencies. The shape of the T(g)(w) patterns is critically influenced by polymer's molecular mass, drug molecule's shape and molecular volume, the type and degree of shielding of hydrogen-bonding capable functional groups, as well as aspects of the preparation process. By altering mixture's T(g) the amorphous solid form of the active ingredient may be retained at ambient or body temperatures, with concomitant improvements in handling, solubility, dissolution rate and oral bioavailability. Given the importance of the problem, the glass transitions observed in pharmaceutical mixtures have been extensively analyzed, aiming to appraise the state of mixing and intermolecular interactions. Here, accumulated experimental information on related systems is re-evaluated and comparably discussed under the light of a more effective and system-inclusive T(g)(w) equation. The present analysis indicates that free volume modifications and conformational changes of the macromolecular chains dominate, over enthalpic effects of mixing, in determining thermal characteristics and crystallization inhibition/retardation. Moreover, hydrogen-bonding and ion-dipole heterocontacts--although favorable of a higher degree of mixing--appear less significant compared to the steric hindrances and the antiplasticization proffered by the higher viscosity component. Copyright © 2011 Elsevier B.V. All rights reserved.

Bayesian Finite Mixtures for Nonlinear Modeling of Educational Data.

ERIC Educational Resources Information Center

Tirri, Henry; And Others

A Bayesian approach for finding latent classes in data is discussed. The approach uses finite mixture models to describe the underlying structure in the data and demonstrate that the possibility of using full joint probability models raises interesting new prospects for exploratory data analysis. The concepts and methods discussed are illustrated…

Development of a Relative Potency Factor (RPF) Approach for Polycyclic Aromatic Hydrocarbon (PAH) Mixtures (Interagency Science Consultation Draft)

EPA Science Inventory

On February 26, 2010, the draft Development of a Relative Potency Factor (RPF) Approach for Polycyclic Aromatic Hydrocarbon (PAH) Mixtures document and the charge to external peer reviewers were released for external peer review and public comment. The draft document and t...

Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

ERIC Educational Resources Information Center

Zhu, Xiaoshu

2013-01-01

The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

Estimating the impact of grouping misclassification on risk prediction when using the relative potency factors method to assess mixtures risk -Presentation

EPA Science Inventory

Environmental health risk assessments of chemical mixtures that rely on component approaches often begin by grouping the chemicals of concern according to toxicological similarity. Approaches that assume dose addition typically are used for groups of similarly-acting chemicals an...

Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures.

PubMed

Oldenkamp, Rik; Hendriks, Harrie W M; van de Meent, Dik; Ragas, Ad M J

2015-09-01

Species in the aquatic environment differ in their toxicological sensitivity to the various chemicals they encounter. In aquatic risk assessment, this interspecies variation is often quantified via species sensitivity distributions. Because the information available for the characterization of these distributions is typically limited, optimal use of information is essential to reduce uncertainty involved in the assessment. In the present study, we show that the credibility intervals on the estimated potentially affected fraction of species after exposure to a mixture of chemicals at environmentally relevant surface water concentrations can be extremely wide if a classical approach is followed, in which each chemical in the mixture is considered in isolation. As an alternative, we propose a hierarchical Bayesian approach, in which knowledge on the toxicity of chemicals other than those assessed is incorporated. A case study with a mixture of 13 pharmaceuticals demonstrates that this hierarchical approach results in more realistic estimations of the potentially affected fraction, as a result of reduced uncertainty in species sensitivity distributions for data-poor chemicals.

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…

Explaining the power-law distribution of human mobility through transportation modality decomposition.

PubMed

Zhao, Kai; Musolesi, Mirco; Hui, Pan; Rao, Weixiong; Tarkoma, Sasu

2015-03-16

Human mobility has been empirically observed to exhibit Lévy flight characteristics and behaviour with power-law distributed jump size. The fundamental mechanisms behind this behaviour has not yet been fully explained. In this paper, we propose to explain the Lévy walk behaviour observed in human mobility patterns by decomposing them into different classes according to the different transportation modes, such as Walk/Run, Bike, Train/Subway or Car/Taxi/Bus. Our analysis is based on two real-life GPS datasets containing approximately 10 and 20 million GPS samples with transportation mode information. We show that human mobility can be modelled as a mixture of different transportation modes, and that these single movement patterns can be approximated by a lognormal distribution rather than a power-law distribution. Then, we demonstrate that the mixture of the decomposed lognormal flight distributions associated with each modality is a power-law distribution, providing an explanation to the emergence of Lévy Walk patterns that characterize human mobility patterns.

Explaining the power-law distribution of human mobility through transportation modality decomposition

NASA Astrophysics Data System (ADS)

Zhao, Kai; Musolesi, Mirco; Hui, Pan; Rao, Weixiong; Tarkoma, Sasu

2015-03-01

Human mobility has been empirically observed to exhibit Lévy flight characteristics and behaviour with power-law distributed jump size. The fundamental mechanisms behind this behaviour has not yet been fully explained. In this paper, we propose to explain the Lévy walk behaviour observed in human mobility patterns by decomposing them into different classes according to the different transportation modes, such as Walk/Run, Bike, Train/Subway or Car/Taxi/Bus. Our analysis is based on two real-life GPS datasets containing approximately 10 and 20 million GPS samples with transportation mode information. We show that human mobility can be modelled as a mixture of different transportation modes, and that these single movement patterns can be approximated by a lognormal distribution rather than a power-law distribution. Then, we demonstrate that the mixture of the decomposed lognormal flight distributions associated with each modality is a power-law distribution, providing an explanation to the emergence of Lévy Walk patterns that characterize human mobility patterns.

Explaining the power-law distribution of human mobility through transportation modality decomposition

PubMed Central

Zhao, Kai; Musolesi, Mirco; Hui, Pan; Rao, Weixiong; Tarkoma, Sasu

2015-01-01

Human mobility has been empirically observed to exhibit Lévy flight characteristics and behaviour with power-law distributed jump size. The fundamental mechanisms behind this behaviour has not yet been fully explained. In this paper, we propose to explain the Lévy walk behaviour observed in human mobility patterns by decomposing them into different classes according to the different transportation modes, such as Walk/Run, Bike, Train/Subway or Car/Taxi/Bus. Our analysis is based on two real-life GPS datasets containing approximately 10 and 20 million GPS samples with transportation mode information. We show that human mobility can be modelled as a mixture of different transportation modes, and that these single movement patterns can be approximated by a lognormal distribution rather than a power-law distribution. Then, we demonstrate that the mixture of the decomposed lognormal flight distributions associated with each modality is a power-law distribution, providing an explanation to the emergence of Lévy Walk patterns that characterize human mobility patterns. PMID:25779306

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Astrophysics Data System (ADS)

Guo, T. H.; Musgrave, J.

1992-11-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Musgrave, J.

1992-01-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

Mixture modelling for cluster analysis.

PubMed

McLachlan, G J; Chang, S U

2004-10-01

Cluster analysis via a finite mixture model approach is considered. With this approach to clustering, the data can be partitioned into a specified number of clusters g by first fitting a mixture model with g components. An outright clustering of the data is then obtained by assigning an observation to the component to which it has the highest estimated posterior probability of belonging; that is, the ith cluster consists of those observations assigned to the ith component (i = 1,..., g). The focus is on the use of mixtures of normal components for the cluster analysis of data that can be regarded as being continuous. But attention is also given to the case of mixed data, where the observations consist of both continuous and discrete variables.

CONDUCTING A RISK ASSESSMENT OF MIXTURES OF DISINFECTION BY-PRODUCTS (DBPS) FOR DRINKING WATER TREATMENT SYSTEMS

EPA Science Inventory

The risk assessment of disinfection by-product (DBP) mixtures in drinking water is an important issue in environmental health. To generate improved assessments of DBP mixture health risk, EPA scientists have explored a number of novel approaches to generating realistic, central ...

Integrated Disinfection By-Products Research: Assessing Reproductive and Developmental Risks Posed by Complex Disinfection By-Product Mixtures

EPA Science Inventory

This article presents a toxicologically-based risk assessment strategy for identifying the individual components or fractions of a complex mixture that are associated with its toxicity. The strategy relies on conventional component-based mixtures risk approaches such as dose addi...

75 FR 54628 - Science Advisory Board Staff Office; Notification of a Public Teleconference of the Science...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-08

... a Public Teleconference of the Science Advisory Board; Polycyclic Aromatic Hydrocarbon (PAH... Hydrocarbon (PAH) Mixtures Review Panel to discuss its draft report on EPA's Development of a Relative Potency Factor (RPF) Approach for Polycyclic Aromatic Hydrocarbon (PAH) Mixtures. DATES: The SAB PAH Mixtures...

Systematic Proteomic Approach to Characterize the Impacts of Chemical Interactions on Protein and Cytotoxicity Responses to Metal Mixture Exposures

EPA Science Inventory

Chemical interactions have posed a big challenge in toxicity characterization and human health risk assessment of environmental mixtures. To characterize the impacts of chemical interactions on protein and cytotoxicity responses to environmental mixtures, we established a systems...

Evaluating the similarity of complex drinking-water disinfection by-product mixtures: overview of the issues.

PubMed

Rice, Glenn E; Teuschler, Linda K; Bull, Richard J; Simmons, Jane E; Feder, Paul I

2009-01-01

Humans are exposed daily to complex mixtures of environmental chemical contaminants, which arise as releases from sources such as engineering procedures, degradation processes, and emissions from mobile or stationary sources. When dose-response data are available for the actual environmental mixture to which individuals are exposed (i.e., the mixture of concern), these data provide the best information for dose-response assessment of the mixture. When suitable data on the mixture itself are not available, surrogate data might be used from a sufficiently similar mixture or a group of similar mixtures. Consequently, the determination of whether the mixture of concern is "sufficiently similar" to a tested mixture or a group of tested mixtures is central to the use of whole mixture methods. This article provides an overview for a series of companion articles whose purpose is to develop a set of biostatistical, chemical, and toxicological criteria and approaches for evaluating the similarity of drinking-water disinfection by-product (DBPs) complex mixtures. Together, the five articles in this series serve as a case study whose techniques will be relevant to assessing similarity for other classes of complex mixtures of environmental chemicals. Schenck et al. (2009) describe the chemistry and mutagenicity of a set of DBP mixtures concentrated from five different drinking-water treatment plants. Bull et al. (2009a, 2009b) describe how the variables that impact the formation of DBP affect the chemical composition and, subsequently, the expected toxicity of the mixture. Feder et al. (2009a, 2009b) evaluate the similarity of DBP mixture concentrates by applying two biostatistical approaches, principal components analysis, and a nonparametric "bootstrap" analysis. Important factors for determining sufficient similarity of DBP mixtures found in this research include disinfectant used; source water characteristics, including the concentrations of bromide and total organic carbon; concentrations and proportions of individual DBPs with known toxicity data on the same endpoint; magnitude of the unidentified fraction of total organic halides; similar toxicity outcomes for whole mixture testing (e.g., mutagenicity); and summary chemical measures such as total trihalomethanes, total haloacetic acids, total haloacetonitriles, and the levels of bromide incorporation in the DBP classes.

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

Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.

PubMed

Bobb, Jennifer F; Valeri, Linda; Claus Henn, Birgit; Christiani, David C; Wright, Robert O; Mazumdar, Maitreyi; Godleski, John J; Coull, Brent A

2015-07-01

Because humans are invariably exposed to complex chemical mixtures, estimating the health effects of multi-pollutant exposures is of critical concern in environmental epidemiology, and to regulatory agencies such as the U.S. Environmental Protection Agency. However, most health effects studies focus on single agents or consider simple two-way interaction models, in part because we lack the statistical methodology to more realistically capture the complexity of mixed exposures. We introduce Bayesian kernel machine regression (BKMR) as a new approach to study mixtures, in which the health outcome is regressed on a flexible function of the mixture (e.g. air pollution or toxic waste) components that is specified using a kernel function. In high-dimensional settings, a novel hierarchical variable selection approach is incorporated to identify important mixture components and account for the correlated structure of the mixture. Simulation studies demonstrate the success of BKMR in estimating the exposure-response function and in identifying the individual components of the mixture responsible for health effects. We demonstrate the features of the method through epidemiology and toxicology applications. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Testing the accuracy of correlations for multicomponent mass transport of adsorbed gases in metal-organic frameworks: diffusion of H2/CH4 mixtures in CuBTC.

PubMed

Keskin, Seda; Liu, Jinchen; Johnson, J Karl; Sholl, David S

2008-08-05

Mass transport of chemical mixtures in nanoporous materials is important in applications such as membrane separations, but measuring diffusion of mixtures experimentally is challenging. Methods that can predict multicomponent diffusion coefficients from single-component data can be extremely useful if these methods are known to be accurate. We present the first test of a method of this kind for molecules adsorbed in a metal-organic framework (MOF). Specifically, we examine the method proposed by Skoulidas, Sholl, and Krishna (SSK) ( Langmuir, 2003, 19, 7977) by comparing predictions made with this method to molecular simulations of mixture transport of H 2/CH 4 mixtures in CuBTC. These calculations provide the first direct information on mixture transport of any species in a MOF. The predictions of the SSK approach are in good agreement with our direct simulations of binary diffusion, suggesting that this approach may be a powerful one for examining multicomponent diffusion in MOFs. We also use our molecular simulation data to test the ideal adsorbed solution theory method for predicting binary adsorption isotherms and a method for predicting mixture self-diffusion coefficients.

Ghost Particle Velocimetry: Accurate 3D Flow Visualization Using Standard Lab Equipment

NASA Astrophysics Data System (ADS)

Buzzaccaro, Stefano; Secchi, Eleonora; Piazza, Roberto

2013-07-01

We describe and test a new approach to particle velocimetry, based on imaging and cross correlating the scattering speckle pattern generated on a near-field plane by flowing tracers with a size far below the diffraction limit, which allows reconstructing the velocity pattern in microfluidic channels without perturbing the flow. As a matter of fact, adding tracers is not even strictly required, provided that the sample displays sufficiently refractive-index fluctuations. For instance, phase separation in liquid mixtures in the presence of shear is suitable to be directly investigated by this “ghost particle velocimetry” technique, which just requires a microscope with standard lamp illumination equipped with a low-cost digital camera. As a further bonus, the peculiar spatial coherence properties of the illuminating source, which displays a finite longitudinal coherence length, allows for a 3D reconstruction of the profile with a resolution of few tenths of microns and makes the technique suitable to investigate turbid samples with negligible multiple scattering effects.

Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes

USGS Publications Warehouse

Elliott, Sarah M.; Brigham, Mark E.; Kiesling, Richard L.; Schoenfuss, Heiko L.; Jorgenson, Zachary G.

2018-01-01

The North American Great Lakes are a vital natural resource that provide fish and wildlife habitat, as well as drinking water and waste assimilation services for millions of people. Tributaries to the Great Lakes receive chemical inputs from various point and nonpoint sources, and thus are expected to have complex mixtures of chemicals. However, our understanding of the co‐occurrence of specific chemicals in complex mixtures is limited. To better understand the occurrence of specific chemical mixtures in the US Great Lakes Basin, surface water from 24 US tributaries to the Laurentian Great Lakes was collected and analyzed for diverse suites of organic chemicals, primarily focused on chemicals of concern (e.g., pharmaceuticals, personal care products, fragrances). A total of 181 samples and 21 chemical classes were assessed for mixture compositions. Basin wide, 1664 mixtures occurred in at least 25% of sites. The most complex mixtures identified comprised 9 chemical classes and occurred in 58% of sampled tributaries. Pharmaceuticals typically occurred in complex mixtures, reflecting pharmaceutical‐use patterns and wastewater facility outfall influences. Fewer mixtures were identified at lake or lake‐influenced sites than at riverine sites. As mixture complexity increased, the probability of a specific mixture occurring more often than by chance greatly increased, highlighting the importance of understanding source contributions to the environment. This empirically based analysis of mixture composition and occurrence may be used to focus future sampling efforts or mixture toxicity assessments. 

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

Cardenas, Rosa E.; Stewart, Kenneth D.; Cowgill, Donald F.

In our study, the authors developed an approach for accurately quantifying the helium content in a gas mixture also containing hydrogen and methane using commercially available getters. The authors performed a systematic study to examine how both H2 and CH4 can be removed simultaneously from the mixture using two SAES St 172® getters operating at different temperatures. The remaining He within the gas mixture can then be measured directly using a capacitance manometer. Moreover, the optimum combination involved operating one getter at 650°C to decompose the methane, and the second at 110°C to remove the hydrogen. Finally, this approach eliminatedmore » the need to reactivate the getters between measurements, thereby enabling multiple measurements to be made within a short time interval, with accuracy better than 1%. The authors anticipate that such an approach will be particularly useful for quantifying the He-3 in mixtures that include tritium, tritiated methane, and helium-3. The presence of tritiated methane, generated by tritium activity, often complicates such measurements.« less

Using natural stand development patterns in artificial mixtures: a case study with cherrybark oak and sweetgum in east-central Mississippi, USA

Treesearch

Brian Roy Lockhart; Andrew W. Ezell; John D. Hodges; Wayne K. Clatterbuck

2006-01-01

Results from a long-term planted mixture of cherrybark oak (Quercus pagoda Raf.) and sweetgum (Liquidambar styraciflua L.) showed sweetgum taller in height and larger in diameter than cherrybark oak early in plantation development. By age 17 years, cherrybark oak was similar in height and diameter with sweetgum and by age 21...

Diversity of developmental patterns in achelate lobsters-today and in the Mesozoic.

PubMed

Haug, Joachim T; Audo, Denis; Charbonnier, Sylvain; Haug, Carolin

2013-11-01

Modern achelate lobsters, slipper and spiny lobsters, have a specific post-embryonic developmental pattern with the following phases: phyllosoma, nisto (slipper lobsters) or puerulus (spiny lobsters), juvenile and adult. The phyllosoma is a peculiar larva, which transforms through a metamorphic moult into another larval form, the nisto or puerulus which largely resembles the juvenile. Unlike the nisto and puerulus, the phyllosoma is characterised by numerous morphological differences to the adult, e.g. a thin head shield, elongate appendages, exopods on these appendages and a special claw. Our reinvestigation of the 85 million years old fossil "Eryoneicus sahelalmae" demonstrates that it represents an unusual type of achelatan lobster larva, characterised by a mixture of phyllosoma and post-phyllosoma characters. We ascribe it to its own genus: Polzicaris nov. gen. We study its significance by comparisons with other cases of Mesozoic fossil larvae also characterised by a mixture of characters. Accordingly, all these larvae are interpreted as ontogenetic intermediates between phyllosoma and post-phyllosoma morphology. Remarkably, most of the larvae show a unique mixture of retained larval and already developed post-larval features. Considering the different-and incompatible-mixture of characters of each of these larvae and their wide geographical and temporal distribution, we interpret all these larvae as belonging to distinct species. The particular character combinations in the different larvae make it currently difficult to reconstruct an evolutionary scenario with a stepwise character acquisition. Yet, it can be concluded that a larger diversity of larval forms and developmental patterns occurred in Mesozoic than in modern faunas.

Two Salix Genotypes Differ in Productivity and Nitrogen Economy When Grown in Monoculture and Mixture

PubMed Central

Hoeber, Stefanie; Fransson, Petra; Prieto-Ruiz, Inés; Manzoni, Stefano; Weih, Martin

2017-01-01

Individual plant species or genotypes often differ in their demand for nutrients; to compete in a community they must be able to acquire more nutrients (i.e., uptake efficiency) and/or use them more efficiently for biomass production than their competitors. These two mechanisms are often complementary, as there are inherent trade-offs between them. In a mixed-stand, species with contrasting nutrient use patterns interact and may use their resources to increase productivity in different ways. Under contrasting nutrient availabilities, the competitive advantages conferred by either strategy may also shift, so that the interaction between resource use strategy and resource availability ultimately determines the performance of individual genotypes in mixtures. The aim was to investigate growth and nitrogen (N) use efficiency of two willow (Salix) genotypes grown in monoculture and mixture in a fertilizer contrast. We explored the hypotheses that (1) the biomass production of at least one of the involved genotypes should be greater when grown in mixture as compared to the corresponding monoculture when nutrients are the most growth-limiting factor; and (2) the N economy of individual genotypes differs when grown in mixture compared to the corresponding monoculture. The genotypes ‘Tora’ (Salix schwerinii ×S. viminalis) and ‘Loden’ (S. dasyclados), with contrasting phenology and functional traits, were grown from cuttings in a growth container experiment under two nutrient fertilization treatments (high and low) in mono- and mixed-culture for 17 weeks. Under low nutrient level, ‘Tora’ showed a higher biomass production (aboveground biomass, leaf area productivity) and N uptake efficiency in mixture than in monoculture, whereas ‘Loden’ showed the opposite pattern. In addition, ‘Loden’ showed higher leaf N productivity but lower N uptake efficiency than ‘Tora.’ The results demonstrated that the specific functional trait combinations of individual genotypes affect their response to mixture as compared to monoculture. Plants grown in mixture as opposed to monoculture may thus increase biomass and vary in their response of N use efficiency traits. However, young plants were investigated here, and as we cannot predict mixture response in mature stands, our results need to be validated at field scale. PMID:28270828

Two Salix Genotypes Differ in Productivity and Nitrogen Economy When Grown in Monoculture and Mixture.

PubMed

Hoeber, Stefanie; Fransson, Petra; Prieto-Ruiz, Inés; Manzoni, Stefano; Weih, Martin

2017-01-01

Individual plant species or genotypes often differ in their demand for nutrients; to compete in a community they must be able to acquire more nutrients (i.e., uptake efficiency) and/or use them more efficiently for biomass production than their competitors. These two mechanisms are often complementary, as there are inherent trade-offs between them. In a mixed-stand, species with contrasting nutrient use patterns interact and may use their resources to increase productivity in different ways. Under contrasting nutrient availabilities, the competitive advantages conferred by either strategy may also shift, so that the interaction between resource use strategy and resource availability ultimately determines the performance of individual genotypes in mixtures. The aim was to investigate growth and nitrogen (N) use efficiency of two willow ( Salix ) genotypes grown in monoculture and mixture in a fertilizer contrast. We explored the hypotheses that (1) the biomass production of at least one of the involved genotypes should be greater when grown in mixture as compared to the corresponding monoculture when nutrients are the most growth-limiting factor; and (2) the N economy of individual genotypes differs when grown in mixture compared to the corresponding monoculture. The genotypes 'Tora' ( Salix schwerinii × S. viminalis ) and 'Loden' ( S. dasyclados ), with contrasting phenology and functional traits, were grown from cuttings in a growth container experiment under two nutrient fertilization treatments (high and low) in mono- and mixed-culture for 17 weeks. Under low nutrient level, 'Tora' showed a higher biomass production (aboveground biomass, leaf area productivity) and N uptake efficiency in mixture than in monoculture, whereas 'Loden' showed the opposite pattern. In addition, 'Loden' showed higher leaf N productivity but lower N uptake efficiency than 'Tora.' The results demonstrated that the specific functional trait combinations of individual genotypes affect their response to mixture as compared to monoculture. Plants grown in mixture as opposed to monoculture may thus increase biomass and vary in their response of N use efficiency traits. However, young plants were investigated here, and as we cannot predict mixture response in mature stands, our results need to be validated at field scale.

Stripe-patterned thermo-responsive cell culture dish for cell separation without cell labeling.

PubMed

Kumashiro, Yoshikazu; Ishihara, Jun; Umemoto, Terumasa; Itoga, Kazuyoshi; Kobayashi, Jun; Shimizu, Tatsuya; Yamato, Masayuki; Okano, Teruo

2015-02-11

A stripe-patterned thermo-responsive surface is prepared to enable cell separation without labeling. The thermo-responsive surface containing a 3 μm striped pattern exhibits various cell adhesion and detachment properties. A mixture of three cell types is separated on the patterned surface based on their distinct cell-adhesion properties, and the composition of the cells is analyzed by flow cytometry. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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…

Theoretical analysis for condensation heat transfer of binary refrigerant mixtures with annular flow in horizontal mini-tubes

NASA Astrophysics Data System (ADS)

Zhang, Hui-Yong; Li, Jun-Ming; Sun, Ji-Liang; Wang, Bu-Xuan

2016-01-01

A theoretical model is developed for condensation heat transfer of binary refrigerant mixtures in mini-tubes with diameter about 1.0 mm. Condensation heat transfer of R410A and R32/R134a mixtures at different mass fluxes and saturated temperatures are analyzed, assuming that the phase flow pattern is annular flow. The results indicate that there exists a maximum interface temperature at the beginning of condensation process for azeotropic and zeotropic mixtures and the corresponding vapor quality to the maximum value increases with mass flux. The effects of mass flux, heat flux, surface tension and tube diameter are analyzed. As expected, the condensation heat transfer coefficients increase with mass flux and vapor quality, and increase faster in high vapor quality region. It is found that the effects of heat flux and surface tension are not so obvious as that of tube diameter. The characteristics of condensation heat transfer of zeotropic mixtures are consistent to those of azeotropic refrigerant mixtures. The condensation heat transfer coefficients increase with the concentration of the less volatile component in binary mixtures.

UP-HILIC-MS/MS to Determine the Action Pattern of Penicillium sp. Dextranase.

PubMed

Yi, Lin; Sun, Xue; Du, Kenze; Ouyang, Yilan; Wu, Chengling; Xu, Naiyu; Linhardt, Robert J; Zhang, Zhenqing

2015-07-01

Investigation of the action pattern of enzymes acting on carbohydrates is challenging, as both the substrate and the digestion products are complex mixtures. Dextran and its enzyme-derived oligosaccharides are widely used for many industrial applications. In this work, a new method relying on ultra-performance hydrophilic interaction liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UP-HILIC-Q/TOF-MS/MS) was developed to analyze a complex mixture of dextran oligosaccharide products to determine the action pattern of dextranase. No derivatization of oligosaccharides was required and the impact of the α- and β-configurations of the native oligosaccharides on the chromatographic separation was eliminated. The 1→6, 1→3, 1→4 backbone linkages and the branch linkages of these oligosaccharides were all distinguished from diagnostic ions in their MS/MS spectra, including fragments corresponding to (0,2)A, (0,3)A, (0,4)A, B-H2O, (2,5)A, and (3,5)A. The sequences of the oligosaccharide products were similarly established. Thus, the complex oligosaccharide mixtures in dextran digestion products were profiled and identified using this method. The more enzyme-resistant structures in dextran were established using much less sample, labor, time, and uncertainty than in previous studies. This method provides an efficient, sensitive, and straightforward way to monitor the entire process of digestion, establish the action pattern of the dextranase from Penicillium sp., and to support the proper industrial application of dextranase.

UP-HILIC-MS/MS to Determine the Action Pattern of Penicillium sp. Dextranase

NASA Astrophysics Data System (ADS)

Yi, Lin; Sun, Xue; Du, Kenze; Ouyang, Yilan; Wu, Chengling; Xu, Naiyu; Linhardt, Robert J.; Zhang, Zhenqing

2015-07-01

Investigation of the action pattern of enzymes acting on carbohydrates is challenging, as both the substrate and the digestion products are complex mixtures. Dextran and its enzyme-derived oligosaccharides are widely used for many industrial applications. In this work, a new method relying on ultra-performance hydrophilic interaction liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UP-HILIC- Q/TOF-MS/MS) was developed to analyze a complex mixture of dextran oligosaccharide products to determine the action pattern of dextranase. No derivatization of oligosaccharides was required and the impact of the α- and β-configurations of the native oligosaccharides on the chromatographic separation was eliminated. The 1→6, 1→3, 1→4 backbone linkages and the branch linkages of these oligosaccharides were all distinguished from diagnostic ions in their MS/MS spectra, including fragments corresponding to 0,2A, 0,3A, 0,4A, B-H2O, 2,5A, and 3,5A. The sequences of the oligosaccharide products were similarly established. Thus, the complex oligosaccharide mixtures in dextran digestion products were profiled and identified using this method. The more enzyme-resistant structures in dextran were established using much less sample, labor, time, and uncertainty than in previous studies. This method provides an efficient, sensitive, and straightforward way to monitor the entire process of digestion, establish the action pattern of the dextranase from Penicillium sp., and to support the proper industrial application of dextranase.

A wire length minimization approach to ocular dominance patterns in mammalian visual cortex

NASA Astrophysics Data System (ADS)

Chklovskii, Dmitri B.; Koulakov, Alexei A.

2000-09-01

The primary visual area (V1) of the mammalian brain is a thin sheet of neurons. Because each neuron is dominated by either right or left eye one can treat V1 as a binary mixture of neurons. The spatial arrangement of neurons dominated by different eyes is known as the ocular dominance (OD) pattern. We propose a theory for OD patterns based on the premise that they are evolutionary adaptations to minimize the length of intra-cortical connections. Thus, the existing OD patterns are obtained by solving a wire length minimization problem. We divide all the neurons into two classes: right- and left-eye dominated. We find that if the number of connections of each neuron with the neurons of the same class differs from that with the other class, the segregation of neurons into monocular regions indeed reduces the wire length. The shape of the regions depends on the relative number of neurons in the two classes. If both classes are equally represented we find that the optimal OD pattern consists of alternating stripes. If one class is less numerous than the other, the optimal OD pattern consists of patches of the underrepresented (ipsilateral) eye dominated neurons surrounded by the neurons of the other class. We predict the transition from stripes to patches when the fraction of neurons dominated by the ipsilateral eye is about 40%. This prediction agrees with the data in macaque and Cebus monkeys. Our theory can be applied to other binary cortical systems.

Thermal conductivity of disperse insulation materials and their mixtures

NASA Astrophysics Data System (ADS)

Geža, V.; Jakovičs, A.; Gendelis, S.; Usiļonoks, I.; Timofejevs, J.

2017-10-01

Development of new, more efficient thermal insulation materials is a key to reduction of heat losses and contribution to greenhouse gas emissions. Two innovative materials developed at Thermeko LLC are Izoprok and Izopearl. This research is devoted to experimental study of thermal insulation properties of both materials as well as their mixture. Results show that mixture of 40% Izoprok and 60% of Izopearl has lower thermal conductivity than pure materials. In this work, material thermal conductivity dependence temperature is also measured. Novel modelling approach is used to model spatial distribution of disperse insulation material. Computational fluid dynamics approach is also used to estimate role of different heat transfer phenomena in such porous mixture. Modelling results show that thermal convection plays small role in heat transfer despite large fraction of air within material pores.

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

PubMed

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

2013-05-30

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

Encoding the local connectivity patterns of fMRI for cognitive task and state classification.

PubMed

Onal Ertugrul, Itir; Ozay, Mete; Yarman Vural, Fatos T

2018-06-15

In this work, we propose a novel framework to encode the local connectivity patterns of brain, using Fisher vectors (FV), vector of locally aggregated descriptors (VLAD) and bag-of-words (BoW) methods. We first obtain local descriptors, called mesh arc descriptors (MADs) from fMRI data, by forming local meshes around anatomical regions, and estimating their relationship within a neighborhood. Then, we extract a dictionary of relationships, called brain connectivity dictionary by fitting a generative Gaussian mixture model (GMM) to a set of MADs, and selecting codewords at the mean of each component of the mixture. Codewords represent connectivity patterns among anatomical regions. We also encode MADs by VLAD and BoW methods using k-Means clustering. We classify cognitive tasks using the Human Connectome Project (HCP) task fMRI dataset and cognitive states using the Emotional Memory Retrieval (EMR). We train support vector machines (SVMs) using the encoded MADs. Results demonstrate that, FV encoding of MADs can be successfully employed for classification of cognitive tasks, and outperform VLAD and BoW representations. Moreover, we identify the significant Gaussians in mixture models by computing energy of their corresponding FV parts, and analyze their effect on classification accuracy. Finally, we suggest a new method to visualize the codewords of the learned brain connectivity dictionary.

Movement patterns and study area boundaries: Influences on survival estimation in capture-mark-recapture studies

USGS Publications Warehouse

Horton, G.E.; Letcher, B.H.

2008-01-01

The inability to account for the availability of individuals in the study area during capture-mark-recapture (CMR) studies and the resultant confounding of parameter estimates can make correct interpretation of CMR model parameter estimates difficult. Although important advances based on the Cormack-Jolly-Seber (CJS) model have resulted in estimators of true survival that work by unconfounding either death or recapture probability from availability for capture in the study area, these methods rely on the researcher's ability to select a method that is correctly matched to emigration patterns in the population. If incorrect assumptions regarding site fidelity (non-movement) are made, it may be difficult or impossible as well as costly to change the study design once the incorrect assumption is discovered. Subtleties in characteristics of movement (e.g. life history-dependent emigration, nomads vs territory holders) can lead to mixtures in the probability of being available for capture among members of the same population. The result of these mixtures may be only a partial unconfounding of emigration from other CMR model parameters. Biologically-based differences in individual movement can combine with constraints on study design to further complicate the problem. Because of the intricacies of movement and its interaction with other parameters in CMR models, quantification of and solutions to these problems are needed. Based on our work with stream-dwelling populations of Atlantic salmon Salmo salar, we used a simulation approach to evaluate existing CMR models under various mixtures of movement probabilities. The Barker joint data model provided unbiased estimates of true survival under all conditions tested. The CJS and robust design models provided similarly unbiased estimates of true survival but only when emigration information could be incorporated directly into individual encounter histories. For the robust design model, Markovian emigration (future availability for capture depends on an individual's current location) was a difficult emigration pattern to detect unless survival and especially recapture probability were high. Additionally, when local movement was high relative to study area boundaries and movement became more diffuse (e.g. a random walk), local movement and permanent emigration were difficult to distinguish and had consequences for correctly interpreting the survival parameter being estimated (apparent survival vs true survival). ?? 2008 The Authors.

Not Quite Normal: Consequences of Violating the Assumption of Normality in Regression Mixture Models

ERIC Educational Resources Information Center

Van Horn, M. Lee; Smith, Jessalyn; Fagan, Abigail A.; Jaki, Thomas; Feaster, Daniel J.; Masyn, Katherine; Hawkins, J. David; Howe, George

2012-01-01

Regression mixture models, which have only recently begun to be used in applied research, are a new approach for finding differential effects. This approach comes at the cost of the assumption that error terms are normally distributed within classes. This study uses Monte Carlo simulations to explore the effects of relatively minor violations of…

Hazard and risk assessment of chemical mixtures using the toxic equivalency factor approach.

PubMed

Safe, S H

1998-08-01

There is considerable public, regulatory, and scientific concern regarding human exposure to endocrine-disrupting chemicals, which include compounds that directly modulate steroid hormone receptor pathways (estrogens, antiestrogens, androgens, antiandrogens) and aryl hydrocarbon receptor (AhR) agonists, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and related compounds. Based on quantitative structure-activity relationships for both AhR and estrogen receptor (ER) agonists, the relative potency (RP) of individual compounds relative to a standard (e.g. TCDD and 17-beta-estradiol) have been determined for several receptor-mediated responses. Therefore, the TCDD or estrogenic equivalent (TEQ or EQ, respectively) of a mixture is defined as TEQ = sigma[T(i)]xRP(i)or EQ=sigma[E(i)]xRP(i), where T(i) and E(i) are concentrations of individual AhR or ER agonists in any mixture. This approach for risk assessment of endocrine-disrupting mixtures assumes that for each endocrine response pathway, the effects of individual compounds are essentially additive. This paper will critically examine the utility of the TEQ/EQ approach for risk assessment, the validity of the assumptions used for this approach, and the problems associated with comparing low dose exposures to xeno and natural (dietary) endocrine disruptors.

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.

Composition, distribution, and potential toxicity of organochlorine mixtures in bed sediments of streams

USGS Publications Warehouse

Phillips, Patrick J.; Nowell, Lisa H.; Gilliom, Robert J.; Nakagaki, Naomi; Murray, Karen; VanAlstyne, Carolyn

2010-01-01

Mixtures of organochlorine compounds have the potential for additive or interactive toxicity to organisms exposed in the stream. This study uses a variety of methods to identify mixtures and a modified concentration-addition approach to estimate their potential toxicity at 845 stream sites across the United States sampled between 1992 and 2001 for organochlorine pesticides and polychlorinated biphenyls (PCBs) in bed sediment. Principal-component (PC) analysis identified five PCs that account for 77% of the total variance in 14 organochlorine compounds in the original dataset. The five PCs represent: (1) chlordane-related compounds and dieldrin; (2) p,p′-DDT and its degradates; (3) o,p′-DDT and its degradates; (4) the pesticide degradates oxychlordane and heptachlor epoxide; and (5) PCBs. The PC analysis grouped compounds that have similar chemical structure (such as parent compound and degradate), common origin (in the same technical pesticide mixture), and(or) similar relation of concentrations to land use. For example, the highest concentrations of chlordane compounds and dieldrin occurred at urban sites, reflecting past use of parent pesticides for termite control. Two approaches to characterizing mixtures—PC-based mixtures and unique mixtures—were applied to all 299 samples with a detection of two or more organochlorine compounds. PC-based mixtures are defined by the presence (in the sample) of one or more compounds associated with that PC. Unique mixtures are defined as a specific combination of two or more compounds detected in a sample, regardless of how many other compounds were also detected in that sample. The simplest PC-based mixtures (containing compounds from 1 or 2 PCs) commonly occurred in a variety of land use settings. Complex mixtures (containing compounds from 3 or more PCs) were most common in samples from urban and mixed/urban sites, especially in the Northeast, reflecting high concentrations of multiple chlordane, dieldrin, DDT-related compounds, and(or) PCBs. The most commonly occurring unique mixture (p,p′-DDE, p,p′-DDD) occurred in both simple and complex PC-based mixtures, and at both urban and agricultural sites. Mean Probable Effect Concentration Quotients (PEC-Q) values, which estimate the potential toxicity of organochlorine contaminant mixtures, were highest for complex mixtures. Mean PEC-Q values were highest for urban sites in the Northeast, followed by mixed/urban sites in the Northeast and agricultural sites in cotton growing areas. These results demonstrate that the PEC-Q approach can be used in combination with PC-based and unique mixture analyses to relate potential aquatic toxicity of contaminant mixtures to mixture complexity, land use, and other surrogates for contaminant sources.

Monitoring Urban Greenness Dynamics Using Multiple Endmember Spectral Mixture Analysis

PubMed Central

Gan, Muye; Deng, Jinsong; Zheng, Xinyu; Hong, Yang; Wang, Ke

2014-01-01

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents’ quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development. PMID:25375176

The application of Gaussian mixture models for signal quantification in MALDI-TOF mass spectrometry of peptides.

PubMed

Spainhour, John Christian G; Janech, Michael G; Schwacke, John H; Velez, Juan Carlos Q; Ramakrishnan, Viswanathan

2014-01-01

Matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) coupled with stable isotope standards (SIS) has been used to quantify native peptides. This peptide quantification by MALDI-TOF approach has difficulties quantifying samples containing peptides with ion currents in overlapping spectra. In these overlapping spectra the currents sum together, which modify the peak heights and make normal SIS estimation problematic. An approach using Gaussian mixtures based on known physical constants to model the isotopic cluster of a known compound is proposed here. The characteristics of this approach are examined for single and overlapping compounds. The approach is compared to two commonly used SIS quantification methods for single compound, namely Peak Intensity method and Riemann sum area under the curve (AUC) method. For studying the characteristics of the Gaussian mixture method, Angiotensin II, Angiotensin-2-10, and Angiotenisn-1-9 and their associated SIS peptides were used. The findings suggest, Gaussian mixture method has similar characteristics as the two methods compared for estimating the quantity of isolated isotopic clusters for single compounds. All three methods were tested using MALDI-TOF mass spectra collected for peptides of the renin-angiotensin system. The Gaussian mixture method accurately estimated the native to labeled ratio of several isolated angiotensin peptides (5.2% error in ratio estimation) with similar estimation errors to those calculated using peak intensity and Riemann sum AUC methods (5.9% and 7.7%, respectively). For overlapping angiotensin peptides, (where the other two methods are not applicable) the estimation error of the Gaussian mixture was 6.8%, which is within the acceptable range. In summary, for single compounds the Gaussian mixture method is equivalent or marginally superior compared to the existing methods of peptide quantification and is capable of quantifying overlapping (convolved) peptides within the acceptable margin of error.

Understanding the human health effects of chemical mixtures.

PubMed Central

Carpenter, David O; Arcaro, Kathleen; Spink, David C

2002-01-01

Most research on the effects of chemicals on biologic systems is conducted on one chemical at a time. However, in the real world people are exposed to mixtures, not single chemicals. Although various substances may have totally independent actions, in many cases two substances may act at the same site in ways that can be either additive or nonadditive. Many even more complex interactions may occur if two chemicals act at different but related targets. In the extreme case there may be synergistic effects, in which case the effects of two substances together are greater than the sum of either effect alone. In reality, most persons are exposed to many chemicals, not just one or two, and therefore the effects of a chemical mixture are extremely complex and may differ for each mixture depending on the chemical composition. This complexity is a major reason why mixtures have not been well studied. In this review we attempt to illustrate some of the principles and approaches that can be used to study effects of mixtures. By the nature of the state of the science, this discussion is more a presentation of what we do not know than of what we do know about mixtures. We approach the study of mixtures at three levels, using specific examples. First, we discuss several human diseases in relation to a variety of environmental agents believed to influence the development and progression of the disease. We present results of selected cellular and animal studies in which simple mixtures have been investigated. Finally, we discuss some of the effects of mixtures at a molecular level. PMID:11834461

Evaluation of forensic DNA mixture evidence: protocol for evaluation, interpretation, and statistical calculations using the combined probability of inclusion.

PubMed

Bieber, Frederick R; Buckleton, John S; Budowle, Bruce; Butler, John M; Coble, Michael D

2016-08-31

The evaluation and interpretation of forensic DNA mixture evidence faces greater interpretational challenges due to increasingly complex mixture evidence. Such challenges include: casework involving low quantity or degraded evidence leading to allele and locus dropout; allele sharing of contributors leading to allele stacking; and differentiation of PCR stutter artifacts from true alleles. There is variation in statistical approaches used to evaluate the strength of the evidence when inclusion of a specific known individual(s) is determined, and the approaches used must be supportable. There are concerns that methods utilized for interpretation of complex forensic DNA mixtures may not be implemented properly in some casework. Similar questions are being raised in a number of U.S. jurisdictions, leading to some confusion about mixture interpretation for current and previous casework. Key elements necessary for the interpretation and statistical evaluation of forensic DNA mixtures are described. Given the most common method for statistical evaluation of DNA mixtures in many parts of the world, including the USA, is the Combined Probability of Inclusion/Exclusion (CPI/CPE). Exposition and elucidation of this method and a protocol for use is the focus of this article. Formulae and other supporting materials are provided. Guidance and details of a DNA mixture interpretation protocol is provided for application of the CPI/CPE method in the analysis of more complex forensic DNA mixtures. This description, in turn, should help reduce the variability of interpretation with application of this methodology and thereby improve the quality of DNA mixture interpretation throughout the forensic community.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

Influence of heavy metals on the formation and the distribution behavior of PAH and PCDD/F during simulated fires.

PubMed

Wobst, M; Wichmann, H; Bahadir, M

2003-04-01

Combustion experiments were performed with an artificial fire load (polystyrene and quartz powder) in a laboratory scale incinerator in the presence of gaseous HCl to simulate accidental fire conditions. The aim of this investigation was to trace back the alterations of the formation and the distribution behavior of PAH and PCDD/PCDF to the presence of CuO or a mixture of metal oxides (CdO, CuO, Fe(2)O(3), PbO, MoO(3), ZnO). The total amount of the 16 PAH target compounds was reduced by the factor of 5-9 when the mixture of metal oxides was present rather than merely CuO. PAH patterns as well as their distribution behavior were significantly influenced by these oxides. In general, transportation inside the installation was enhanced for most of the 16 analyzed PAH. Only fluorene and dibenzo[a,h]anthracene were transported to a smaller extent. In contrast to PAH, total concentrations of PCDD were increased by factor 9 and of PCDF by factor 10, respectively, when CuO was present. Adding the mixture of metal oxides resulted in an increase of PCDD by factor 14 and of PCDF by factor 7. CuO and the mixture of metal oxides had a different influence on the PCDD/F homologue patterns. For instance, the HxCDF to OCDF ratio after incineration without any metal oxide was 1 to 6, whereas addition of CuO or the mixture of the metal oxides shifted the HxCDF to OCDF ratios towards 1 to 40 or 1 to 17, respectively. Combustion along with CuO increased transportation of higher chlorinated PCDF congeners, whereas the mixture of the metal oxides caused a strong decrease of PCDF distribution throughout the system.

Controlled irrigation of a structured packing as a method for increasing the efficiency of liquid mixture separation in the distillation column

NASA Astrophysics Data System (ADS)

Pavlenko, A. N.; Zhukov, V. E.; Pecherkin, N. I.; Nazarov, A. D.; Li, X.; Li, H.; Gao, X.; Sui, H.

2017-09-01

The use of modern structured packing in the distillation columns allows much more even distribution of the liquid film over the packing surface, but it does not completely solve the problem of uniform distribution of flow parameters over the entire height of the packing. Negative stratification of vapor along the packing height caused by different densities of vapor mixture components and higher temperature in the lower part of the column leads to formation of large-scale maldistributions of temperature and mixture composition over the column cross-section even under the conditions of uniform irrigation of packing with liquid. In these experiments, the idea of compensatory action of liquid distributor on the large-scale maldistribution of mixture composition over the column cross-section was implemented. The experiments were carried out in the distillation column with the diameter of 0.9 m on 10 layers of the Mellapak 350Y packing with the total height of 2.1 m. The mixture of R-21 and R-114 was used as the working mixture. To irrigate the packing, the liquid distributorr with 126 independently controlled solenoid valves overlapping the holes with the diameter of 5 mm, specially designed by the authors, was used. Response of the column to the action of liquid distributor was observed in real time according to the indications of 3 groups of thermometers mounted in 3 different cross-sections of the column. The experiments showed that the minimal correction of the drip point pattern in the controlled liquid distributor can significantly affect the pattern of flow parameter distribution over the cross-section and height of the mass transfer surface and increase separation efficiency of the column within 20%.

Influence of deposition and spray pattern of nasal powders on insulin bioavailability.

PubMed

Pringels, E; Callens, C; Vervaet, C; Dumont, F; Slegers, G; Foreman, P; Remon, J P

2006-03-09

The influence of the deposition pattern and spray characteristics of nasal powder formulations on the insulin bioavailability was investigated in rabbits. The formulations were prepared by freeze drying a dispersion containing a physical mixture of drum dried waxy maize starch (DDWM)/Carbopol 974P (90/10, w/w) or a spray-dried mixture of Amioca starch/Carbopol 974P (25/75, w/w). The deposition in the nasal cavity of rabbits and in a silicone human nose model after actuation of three nasal delivery devices (Monopowder, Pfeiffer and experimental system) was compared and related to the insulin bioavailability. Posterior deposition of the powder formulation in the nasal cavity lowered the insulin bioavailability. To study the spray pattern, the shape and cross-section of the emitted powder cloud were analysed. It was concluded that the powder bulk density of the formulation influenced the spray pattern. Consequently, powders of different bulk density were prepared by changing the solid fraction of the freeze dried dispersion and by changing the freezing rate during freeze drying. After nasal delivery of these powder formulations no influence of the powder bulk density and of the spray pattern on the insulin bioavailability was observed.

On the clustering of multidimensional pictorial data

NASA Technical Reports Server (NTRS)

Bryant, J. D. (Principal Investigator)

1979-01-01

Obvious approaches to reducing the cost (in computer resources) of applying current clustering techniques to the problem of remote sensing are discussed. The use of spatial information in finding fields and in classifying mixture pixels is examined, and the AMOEBA clustering program is described. Internally, a pattern recognition program, from without, AMOEBA appears to be an unsupervised clustering program. It is fast and automatic. No choices (such as arbitrary thresholds to set split/combine sequences) need be made. The problem of finding the number of clusters is solved automatically. At the conclusion of the program, all points in the scene are classified; however, a provision is included for a reject classification of some points which, within the theoretical framework, cannot rationally be assigned to any cluster.

College drinking behaviors: mediational links between parenting styles, impulse control, and alcohol-related outcomes.

PubMed

Patock-Peckham, Julie A; Morgan-Lopez, Antonio A

2006-06-01

Mediational links between parenting styles (authoritative, authoritarian, permissive), impulsiveness (general control), drinking control (specific control), and alcohol use and abuse were tested. A pattern-mixture approach (for modeling non-ignorable missing data) with multiple-group structural equation models with 421 (206 female, 215 male) college students was used. Gender was examined as a potential moderator of parenting styles on control processes related to drinking. Specifically, the parent-child gender match was found to have implications for increased levels of impulsiveness (a significant mediator of parenting effects on drinking control). These findings suggest that a parent with a permissive parenting style who is the same gender as the respondent can directly influence control processes and indirectly influence alcohol use and abuse.

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.

An approach of characterizing the degree of spatial color mixture

NASA Astrophysics Data System (ADS)

Chu, Miao; Tian, Shaohui

2017-07-01

The digital camouflage technology arranges different color mosaics according to a certain rules, compared with traditional camouflage, it has more outstanding results deal with different distance reconnaissance. The better result of digital camouflage is mainly attributed to spatial color mixture, and is also a key factor to improve digital camouflage design. However, the research of space color mixture is relatively lack, cannot provide inadequate support for digital camouflage design. Therefore, according to the process of spatial color mixture, this paper proposes an effective parameter, spatial-color-mixture ratio, to characterize the degree of spatial color mixture. The experimental results show that spatial-color-mixture ratio is feasible and effective in practice, which could provide a new direction for further research on digital camouflage.

Interactions of a pesticide/heavy metal mixture in marine bivalves: a transcriptomic assessment

PubMed Central

2011-01-01

Background Mixtures of chemicals present in aquatic environments may elicit toxicity due to additive or synergistic effects among the constituents or, vice versa, the adverse outcome may be reduced by antagonistic interactions. Deviations from additivity should be explained either by the perturbations of toxicokinetic parameters and/or chemical toxicodynamics. We addressed this important question in marine mussels exposed subchronically to a binary mixture made of two wide-spread pollutants: the heavy metal nickel and the organic phosphorus pesticide Chlorpyrifos. To this aim, we carried out in tissues of Mytius galloprovincialis (Lam) a systems approach based on the evaluation and integration of different disciplines, i.e. high throughput gene expression profiling, functional genomics, stress biomakers and toxicokinetics. Results Cellular and tissue biomarkers, viz. digestive gland lysosomal membrane stability, lysosomal/cytosol volume ratio, neutral lipid content and gill acetylcholinesterase activity were, in general, altered by either the exposure to nickel and Chlorpyrifos. However, their joint action rendered (i) an overall decrease of the stress syndrome level, as evaluated through an expert system integrating biomarkers and (ii) statistically significant antagonistic deviations from the reference model systems to predict mixture toxicity. While toxicokinetic modeling did not explain mixture interactions, gene expression profiling and further Gene Ontology-based functional genomics analysis provided clues that the decrement of toxicity may arise from the development of specific toxicodynamics. Multivariate statistics of microarray data (238 genes in total, representing about 14% of the whole microarray catalogue) showed two separate patterns for the single chemicals: the one belonging to the heavy metal -135 differentially expressed genes (DEGs) was characterized by the modulation of transcript levels involved in nucleic acid metabolism, cell proliferation and lipid metabolic processes. Chlorpyrifos exposure (43 DEGs) yielded a molecular signature which was biased towards carbohydrate catabolism (indeed, chitin metabolism) and developmental processes. The exposure to the mixture (103 DEGs) elicited a composite complex profile which encompassed the core properties of the pesticide but also a relevant set of unique features. Finally, the relative mRNA abundance of twelve genes was followed by Q-PCR to either confirm or complement microarray data. These results, in general, were compatible with those from arrays and indeed confirmed the association of the relative abundance of two GM-2 ganglioside activator genes in the development of the hyperlipidosis syndrome observed in digestive gland lysosomes of single chemical exposed mussels. Conclusion The transcriptomic assessment fitted with biological data to indicate the occurrence of different toxicodynamic events and, in general, a decrease of toxicity, driven by the mitigation or even abolition of lysosomal responses. Furthermore, our results emphasized the importance of the application of mechanistic approaches and the power of systems assessment to study toxicological responses in ecologically relevant organisms. PMID:21496282

Interactions of a pesticide/heavy metal mixture in marine bivalves: a transcriptomic assessment.

PubMed

Dondero, Francesco; Banni, Mohamed; Negri, Alessandro; Boatti, Lara; Dagnino, Alessandro; Viarengo, Aldo

2011-04-16

Mixtures of chemicals present in aquatic environments may elicit toxicity due to additive or synergistic effects among the constituents or, vice versa, the adverse outcome may be reduced by antagonistic interactions. Deviations from additivity should be explained either by the perturbations of toxicokinetic parameters and/or chemical toxicodynamics. We addressed this important question in marine mussels exposed subchronically to a binary mixture made of two wide-spread pollutants: the heavy metal nickel and the organic phosphorus pesticide Chlorpyrifos. To this aim, we carried out in tissues of Mytius galloprovincialis (Lam) a systems approach based on the evaluation and integration of different disciplines, i.e. high throughput gene expression profiling, functional genomics, stress biomakers and toxicokinetics. Cellular and tissue biomarkers, viz. digestive gland lysosomal membrane stability, lysosomal/cytosol volume ratio, neutral lipid content and gill acetylcholinesterase activity were, in general, altered by either the exposure to nickel and Chlorpyrifos. However, their joint action rendered (i) an overall decrease of the stress syndrome level, as evaluated through an expert system integrating biomarkers and (ii) statistically significant antagonistic deviations from the reference model systems to predict mixture toxicity. While toxicokinetic modeling did not explain mixture interactions, gene expression profiling and further Gene Ontology-based functional genomics analysis provided clues that the decrement of toxicity may arise from the development of specific toxicodynamics. Multivariate statistics of microarray data (238 genes in total, representing about 14% of the whole microarray catalogue) showed two separate patterns for the single chemicals: the one belonging to the heavy metal -135 differentially expressed genes (DEGs) was characterized by the modulation of transcript levels involved in nucleic acid metabolism, cell proliferation and lipid metabolic processes. Chlorpyrifos exposure (43 DEGs) yielded a molecular signature which was biased towards carbohydrate catabolism (indeed, chitin metabolism) and developmental processes. The exposure to the mixture (103 DEGs) elicited a composite complex profile which encompassed the core properties of the pesticide but also a relevant set of unique features. Finally, the relative mRNA abundance of twelve genes was followed by Q-PCR to either confirm or complement microarray data. These results, in general, were compatible with those from arrays and indeed confirmed the association of the relative abundance of two GM-2 ganglioside activator genes in the development of the hyperlipidosis syndrome observed in digestive gland lysosomes of single chemical exposed mussels. The transcriptomic assessment fitted with biological data to indicate the occurrence of different toxicodynamic events and, in general, a decrease of toxicity, driven by the mitigation or even abolition of lysosomal responses. Furthermore, our results emphasized the importance of the application of mechanistic approaches and the power of systems assessment to study toxicological responses in ecologically relevant organisms.

Green Chemistry Challenge: 2017 Academic Award

EPA Pesticide Factsheets

Green Chemistry Challenge 2017 award winner, Professor Schelter, developed a new, targeted approach for separating mixtures of rare earth metals obtained from consumer waste streams comprising mixtures of Nd/Dy and Eu/Y

Development of an Image-based Multi-Scale Finite Element Approach to Predict Fatigue Damage in Asphalt Mixtures

NASA Astrophysics Data System (ADS)

Arshadi, Amir

Image-based simulation of complex materials is a very important tool for understanding their mechanical behavior and an effective tool for successful design of composite materials. In this thesis an image-based multi-scale finite element approach is developed to predict the mechanical properties of asphalt mixtures. In this approach the "up-scaling" and homogenization of each scale to the next is critically designed to improve accuracy. In addition to this multi-scale efficiency, this study introduces an approach for consideration of particle contacts at each of the scales in which mineral particles exist. One of the most important pavement distresses which seriously affects the pavement performance is fatigue cracking. As this cracking generally takes place in the binder phase of the asphalt mixture, the binder fatigue behavior is assumed to be one of the main factors influencing the overall pavement fatigue performance. It is also known that aggregate gradation, mixture volumetric properties, and filler type and concentration can affect damage initiation and progression in the asphalt mixtures. This study was conducted to develop a tool to characterize the damage properties of the asphalt mixtures at all scales. In the present study the Viscoelastic continuum damage model is implemented into the well-known finite element software ABAQUS via the user material subroutine (UMAT) in order to simulate the state of damage in the binder phase under the repeated uniaxial sinusoidal loading. The inputs are based on the experimentally derived measurements for the binder properties. For the scales of mastic and mortar, the artificially 2-Dimensional images of mastic and mortar scales were generated and used to characterize the properties of those scales. Finally, the 2D scanned images of asphalt mixtures are used to study the asphalt mixture fatigue behavior under loading. In order to validate the proposed model, the experimental test results and the simulation results were compared. Indirect tensile fatigue tests were conducted on asphalt mixture samples. A comparison between experimental results and the results from simulation shows that the model developed in this study is capable of predicting the effect of asphalt binder properties and aggregate micro-structure on mechanical behavior of asphalt concrete under loading.

Thermal gravitational separation of ternary mixture n-dodecane/isobutylbenzene/tetralin components in a porous medium

NASA Astrophysics Data System (ADS)

Larabi, Mohamed Aziz; Mutschler, Dimitri; Mojtabi, Abdelkader

2016-06-01

Our present work focuses on the coupling between thermal diffusion and convection in order to improve the thermal gravitational separation of mixture components. The separation phenomenon was studied in a porous medium contained in vertical columns. We performed analytical and numerical simulations to corroborate the experimental measurements of the thermal diffusion coefficients of ternary mixture n-dodecane, isobutylbenzene, and tetralin obtained in microgravity in the international space station. Our approach corroborates the existing data published in the literature. The authors show that it is possible to quantify and to optimize the species separation for ternary mixtures. The authors checked, for ternary mixtures, the validity of the "forgotten effect hypothesis" established for binary mixtures by Furry, Jones, and Onsager. Two complete and different analytical resolution methods were used in order to describe the separation in terms of Lewis numbers, the separation ratios, the cross-diffusion coefficients, and the Rayleigh number. The analytical model is based on the parallel flow approximation. In order to validate this model, a numerical simulation was performed using the finite element method. From our new approach to vertical separation columns, new relations for mass fraction gradients and the optimal Rayleigh number for each component of the ternary mixture were obtained.

A Multi-targeted Approach to Suppress Tumor-Promoting Inflammation

PubMed Central

Samadi, Abbas K.; Georgakilas, Alexandros G.; Amedei, Amedeo; Amin, Amr; Bishayee, Anupam; Lokeshwar, Bal L.; Grue, Brendan; Panis, Carolina; Boosani, Chandra S.; Poudyal, Deepak; Stafforini, Diana M.; Bhakta, Dipita; Niccolai, Elena; Guha, Gunjan; Rupasinghe, H.P. Vasantha; Fujii, Hiromasa; Honoki, Kanya; Mehta, Kapil; Aquilano, Katia; Lowe, Leroy; Hofseth, Lorne J.; Ricciardiello, Luigi; Ciriolo, Maria Rosa; Singh, Neetu; Whelan, Richard L.; Chaturvedi, Rupesh; Ashraf, S. Salman; Kumara, HMC Shantha; Nowsheen, Somaira; Mohammed, Sulma I.; Helferich, William G.; Yang, Xujuan

2015-01-01

Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-kappaB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes. PMID:25951989

Detection of illicit drugs with the technique of spectral fluorescence signatures (SFS)

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Babichenko, Sergey

2010-10-01

The SFS technology has already proved its analytical capabilities in a variety of industrial and environmental tasks. Recently it has been introduced for forensic applications. The key features of the SFS method - measuring a 3-dimensional spectrum of fluorescence of the sample (intensity versus excitation and emission wavelengths) with following recognition of specific spectral patterns of SFS responsible for individual drugs - provide an effective tool for the analysis of untreated seized samples, without any separation of the substance of interest from its mixture with accompanying cutting agents and diluents as a preparatory step. In such approach the chemical analysis of the sample is substituted by the analysis of SFS matrix visualized as an optical image. The SFS technology of drug detection is realized by NarTest® NTX2000 analyzer, compact device intended to measure suspicious samples in liquid, solid and powder forms. It simplifies the detection process due to fully automated procedures of SFS measuring and integrated expert system for recognition of spectral patterns. Presently the expert system of NTX2000 is able to detect marijuana, cocaine, heroin, MDMA, amphetamine and methamphetamine with the detection limit down to 5% of the drug concentration in various mixtures. The numerous tests with street samples confirmed that the use of SFS method provides reliable results with high sensitivity and selectivity for identification of drugs of abuse. More than 3000 street samples of the aforesaid drugs were analyzed with NTX2000 during validation process, and the correspondence of SFS results and conclusions of standard forensic analyses with GC/MS techniques was in 99.4% cases.

Bottom-up coarse-grained models with predictive accuracy and transferability for both structural and thermodynamic properties of heptane-toluene mixtures

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

Dunn, Nicholas J. H.; Noid, W. G., E-mail: wnoid@chem.psu.edu

This work investigates the promise of a “bottom-up” extended ensemble framework for developing coarse-grained (CG) models that provide predictive accuracy and transferability for describing both structural and thermodynamic properties. We employ a force-matching variational principle to determine system-independent, i.e., transferable, interaction potentials that optimally model the interactions in five distinct heptane-toluene mixtures. Similarly, we employ a self-consistent pressure-matching approach to determine a system-specific pressure correction for each mixture. The resulting CG potentials accurately reproduce the site-site rdfs, the volume fluctuations, and the pressure equations of state that are determined by all-atom (AA) models for the five mixtures. Furthermore, we demonstratemore » that these CG potentials provide similar accuracy for additional heptane-toluene mixtures that were not included their parameterization. Surprisingly, the extended ensemble approach improves not only the transferability but also the accuracy of the calculated potentials. Additionally, we observe that the required pressure corrections strongly correlate with the intermolecular cohesion of the system-specific CG potentials. Moreover, this cohesion correlates with the relative “structure” within the corresponding mapped AA ensemble. Finally, the appendix demonstrates that the self-consistent pressure-matching approach corresponds to minimizing an appropriate relative entropy.« less

Bottom-up coarse-grained models with predictive accuracy and transferability for both structural and thermodynamic properties of heptane-toluene mixtures.

PubMed

Dunn, Nicholas J H; Noid, W G

2016-05-28

This work investigates the promise of a "bottom-up" extended ensemble framework for developing coarse-grained (CG) models that provide predictive accuracy and transferability for describing both structural and thermodynamic properties. We employ a force-matching variational principle to determine system-independent, i.e., transferable, interaction potentials that optimally model the interactions in five distinct heptane-toluene mixtures. Similarly, we employ a self-consistent pressure-matching approach to determine a system-specific pressure correction for each mixture. The resulting CG potentials accurately reproduce the site-site rdfs, the volume fluctuations, and the pressure equations of state that are determined by all-atom (AA) models for the five mixtures. Furthermore, we demonstrate that these CG potentials provide similar accuracy for additional heptane-toluene mixtures that were not included their parameterization. Surprisingly, the extended ensemble approach improves not only the transferability but also the accuracy of the calculated potentials. Additionally, we observe that the required pressure corrections strongly correlate with the intermolecular cohesion of the system-specific CG potentials. Moreover, this cohesion correlates with the relative "structure" within the corresponding mapped AA ensemble. Finally, the appendix demonstrates that the self-consistent pressure-matching approach corresponds to minimizing an appropriate relative entropy.

Modeling of Complex Mixtures: JP-8 Toxicokinetics

DTIC Science & Technology

2008-10-01

generic tissue compartments in which we have combined diffusion limitation and deep tissue (global tissue model). We also applied a QSAR approach for...SUBJECT TERMS jet fuel, JP-8, PBPK modeling, complex mixtures, nonane, decane, naphthalene, QSAR , alternative fuels 16. SECURITY CLASSIFICATION OF...necessary, to apply to the interaction of specific compounds with specific tissues. We have also applied a QSAR approach for estimating blood and tissue

Separation processes using expulsion from dilute supercritical solutions

DOEpatents

Cochran, Jr., Henry D.

1993-01-01

A process for separating isotopes as well as other mixtures by utilizing the behavior of dilute repulsive or weakly attractive elements of the mixtures as the critical point of the solvent is approached.

Interim Policy for Evaluation of Stereoisomeric Pesticides

EPA Pesticide Factsheets

An interim approach for determining data requirements for non-racemic mixtures of stereoisomeric pesticides. These data are needed in order to assess the risk posed to ecosystems and drinking water sources by these mixtures.

Bi-scale analysis of multitemporal land cover fractions for wetland vegetation mapping

NASA Astrophysics Data System (ADS)

Michishita, Ryo; Jiang, Zhiben; Gong, Peng; Xu, Bing

2012-08-01

Land cover fractions (LCFs) derived through spectral mixture analysis are useful in understanding sub-pixel information. However, few studies have been conducted on the analysis of time-series LCFs. Although multi-scale comparisons of spectral index, hard classification, and land surface temperature images have received attention, rarely have these approaches been applied to LCFs. This study compared the LCFs derived through Multiple Endmember Spectral Mixture Analysis (MESMA) using the time-series Landsat Thematic Mapper (TM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired in the Poyang Lake area, China between 2004 and 2005. Specifically, we aimed to: (1) propose an approach for optimal endmember (EM) selection in time-series MESMA; (2) understand the trends in time-series LCFs derived from the TM and MODIS data; and (3) examine the trends in the correlation between the bi-scale LCFs derived from the time-series TM and MODIS data. Our results indicated: (1) the EM spectra chosen according to the proposed hierarchical three-step approach (overall, seasonal, and individual) accurately modeled the both the TM and MODIS images; (2) green vegetation (GV) and NPV/soil/impervious surface (N/S/I) classes followed sine curve trends in the overall area, while the two water classes displayed the water level change pattern in the areas primarily covered with wetland vegetation; and (3) GV, N/S/I, and bright water classes indicated a moderately high agreement between the TM and MODIS LCFs in the whole area (adjusted R2 ⩾ 0.6). However, low levels of correlations were found in the areas primarily dominated by wetland vegetation for all land cover classes.

The Mathematics of a Successful Deconvolution: A Quantitative Assessment of Mixture-Based Combinatorial Libraries Screened Against Two Formylpeptide Receptors

PubMed Central

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

2014-01-01

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays. PMID:23722730

Growth Mixture Modeling of Academic Achievement in Children of Varying Birth Weight Risk

PubMed Central

Espy, Kimberly Andrews; Fang, Hua; Charak, David; Minich, Nori; Taylor, H. Gerry

2009-01-01

The extremes of birth weight and preterm birth are known to result in a host of adverse outcomes, yet studies to date largely have used cross-sectional designs and variable-centered methods to understand long-term sequelae. Growth mixture modeling (GMM) that utilizes an integrated person- and variable-centered approach was applied to identify latent classes of achievement from a cohort of school-age children born at varying birth weights. GMM analyses revealed two latent achievement classes for calculation, problem-solving, and decoding abilities. The classes differed substantively and persistently in proficiency and in growth trajectories. Birth weight was a robust predictor of class membership for the two mathematics achievement outcomes and a marginal predictor of class membership for decoding. Neither visuospatial-motor skills nor environmental risk at study entry added to class prediction for any of the achievement skills. Among children born preterm, neonatal medical variables predicted class membership uniquely beyond birth weight. More generally, GMM is useful in revealing coherence in the developmental patterns of academic achievement in children of varying weight at birth, and is well suited to investigations of sources of heterogeneity. PMID:19586210

Semi-supervised anomaly detection - towards model-independent searches of new physics

NASA Astrophysics Data System (ADS)

Kuusela, Mikael; Vatanen, Tommi; Malmi, Eric; Raiko, Tapani; Aaltonen, Timo; Nagai, Yoshikazu

2012-06-01

Most classification algorithms used in high energy physics fall under the category of supervised machine learning. Such methods require a training set containing both signal and background events and are prone to classification errors should this training data be systematically inaccurate for example due to the assumed MC model. To complement such model-dependent searches, we propose an algorithm based on semi-supervised anomaly detection techniques, which does not require a MC training sample for the signal data. We first model the background using a multivariate Gaussian mixture model. We then search for deviations from this model by fitting to the observations a mixture of the background model and a number of additional Gaussians. This allows us to perform pattern recognition of any anomalous excess over the background. We show by a comparison to neural network classifiers that such an approach is a lot more robust against misspecification of the signal MC than supervised classification. In cases where there is an unexpected signal, a neural network might fail to correctly identify it, while anomaly detection does not suffer from such a limitation. On the other hand, when there are no systematic errors in the training data, both methods perform comparably.

High-Resolution Numerical Simulation and Analysis of Mach Reflection Structures in Detonation Waves in Low-Pressure H 2 –O 2 –Ar Mixtures: A Summary of Results Obtained with the Adaptive Mesh Refinement Framework AMROC

DOE PAGES

Deiterding, Ralf

2011-01-01

Numerical simulation can be key to the understanding of the multidimensional nature of transient detonation waves. However, the accurate approximation of realistic detonations is demanding as a wide range of scales needs to be resolved. This paper describes a successful solution strategy that utilizes logically rectangular dynamically adaptive meshes. The hydrodynamic transport scheme and the treatment of the nonequilibrium reaction terms are sketched. A ghost fluid approach is integrated into the method to allow for embedded geometrically complex boundaries. Large-scale parallel simulations of unstable detonation structures of Chapman-Jouguet detonations in low-pressure hydrogen-oxygen-argon mixtures demonstrate the efficiency of the described techniquesmore » in practice. In particular, computations of regular cellular structures in two and three space dimensions and their development under transient conditions, that is, under diffraction and for propagation through bends are presented. Some of the observed patterns are classified by shock polar analysis, and a diagram of the transition boundaries between possible Mach reflection structures is constructed.« less

Identification of degenerate neuronal systems based on intersubject variability.

PubMed

Noppeney, Uta; Penny, Will D; Price, Cathy J; Flandin, Guillaume; Friston, Karl J

2006-04-15

Group studies implicitly assume that all subjects activate one common system to sustain a particular cognitive task. Intersubject variability is generally treated as well-behaved and uninteresting noise. However, intersubject variability might result from subjects engaging different degenerate neuronal systems that are each sufficient for task performance. This would produce a multimodal distribution of intersubject variability. We have explored this idea with the help of Gaussian Mixture Modeling and Bayesian model comparison procedures. We illustrate our approach using a crossmodal priming paradigm, in which subjects perform a semantic decision on environmental sounds or their spoken names that were preceded by a semantically congruent or incongruent picture or written name. All subjects consistently activated the superior temporal gyri bilaterally, the left fusiform gyrus and the inferior frontal sulcus. Comparing a One and Two Gaussian Mixture Model of the unexplained residuals provided very strong evidence for two groups with distinct activation patterns: 6 subjects exhibited additional activations in the superior temporal sulci bilaterally, the right superior frontal and central sulcus. 11 subjects showed increased activation in the striate and the right inferior parietal cortex. These results suggest that semantic decisions on auditory-visual compound stimuli might be accomplished by two overlapping degenerate neuronal systems.

A discrete mathematical model applied to genetic regulation and metabolic networks.

PubMed

Asenjo, A J; Ramirez, P; Rapaport, I; Aracena, J; Goles, E; Andrews, B A

2007-03-01

This paper describes the use of a discrete mathematical model to represent the basic mechanisms of regulation of the bacteria E. coli in batch fermentation. The specific phenomena studied were the changes in metabolism and genetic regulation when the bacteria use three different carbon substrates (glucose, glycerol, and acetate). The model correctly predicts the behavior of E. coli vis-à-vis substrate mixtures. In a mixture of glucose, glycerol, and acetate, it prefers glucose, then glycerol, and finally acetate. The model included 67 nodes; 28 were genes, 20 enzymes, and 19 regulators/biochemical compounds. The model represents both the genetic regulation and metabolic networks in an inrtegrated form, which is how they function biologically. This is one of the first attempts to include both of these networks in one model. Previously, discrete mathematical models were used only to describe genetic regulation networks. The study of the network dynamics generated 8 (2(3)) fixed points, one for each nutrient configuration (substrate mixture) in the medium. The fixed points of the discrete model reflect the phenotypes described. Gene expression and the patterns of the metabolic fluxes generated are described accurately. The activation of the gene regulation network depends basically on the presence of glucose and glycerol. The model predicts the behavior when mixed carbon sources are utilized as well as when there is no carbon source present. Fictitious jokers (Joker1, Joker2, and Repressor SdhC) had to be created to control 12 genes whose regulation mechanism is unknown, since glycerol and glucose do not act directly on the genes. The approach presented in this paper is particularly useful to investigate potential unknown gene regulation mechanisms; such a novel approach can also be used to describe other gene regulation situations such as the comparison between non-recombinant and recombinant yeast strain, producing recombinant proteins, presently under investigation in our group.

Impact of rainfall patterns and frequency on the export of pesticides and heavy-metals from agricultural soils.

PubMed

Meite, Fatima; Alvarez-Zaldívar, Pablo; Crochet, Alexandre; Wiegert, Charline; Payraudeau, Sylvain; Imfeld, Gwenaël

2018-03-01

The combined influence of soil characteristics, pollutant aging and rainfall patterns on the export of pollutants from topsoils is poorly understood. We used laboratory experiments and parsimonious modeling to evaluate the impact of rainfall characteristics on the ponding and the leaching of a pollutant mixture from topsoils. The mixture included the fungicide metalaxyl, the herbicide S-metolachlor, as well as copper (Cu) and zinc (Zn). Four rainfall patterns, which differed in their durations and intensities, were applied twice successively with a 7days interval on each soil type. To evaluate the influence of soil type and aging, experiments included crop and vineyard soils and two stages of pollutant aging (0 and 10days). The global export of pollutants was significantly controlled by the rainfall duration and frequency (P<0.01). During the first rainfall event, the longest and most intense rainfall pattern yielded the largest export of metalaxyl (44.5±21.5% of the initial mass spiked in the soils), S-metolachlor (8.1±3.1%) and Cu (3.1±0.3%). Soil compaction caused by the first rainfall reduced in the second rainfall the leaching of remaining metalaxyl, S-metolachlor, Cu and Zn by 2.4-, 2.9-, 30- and 50-fold, respectively. In contrast, soil characteristics and aging had less influence on pollutant mass export. The soil type significantly influenced the leaching of Zn, while short-term aging impacted Cu leaching. Our results suggest that rainfall characteristics predominantly control export patterns of metalaxyl and S-metolachlor, in particular when the aging period is short. We anticipate our study to be a starting point for more systematic evaluation of the dissolved pollutant ponding/leaching partitioning and the export of pollutant mixtures from different soil types in relation to rainfall patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

Solution combustion synthesis of strontium aluminate, SrAl2O4, powders: single-fuel versus fuel-mixture approach.

PubMed

Ianoş, Robert; Istratie, Roxana; Păcurariu, Cornelia; Lazău, Radu

2016-01-14

The solution combustion synthesis of strontium aluminate, SrAl2O4, via the classic single-fuel approach and the modern fuel-mixture approach was investigated in relation to the synthesis conditions, powder properties and thermodynamic aspects. The single-fuel approach (urea or glycine) did not yield SrAl2O4 directly from the combustion reaction. The absence of SrAl2O4 was explained by the low amount of energy released during the combustion process, in spite of the highly negative values of the standard enthalpy of reaction and standard Gibbs free energy. In the case of single-fuel recipes, the maximum combustion temperatures measured by thermal imaging (482 °C - urea, 941 °C - glycine) were much lower than the calculated adiabatic temperatures (1864 °C - urea, 2147 °C - glycine). The fuel-mixture approach (urea and glycine) clearly represented a better option, since (α,β)-SrAl2O4 resulted directly from the combustion reaction. The maximum combustion temperature measured in the case of a urea and glycine fuel mixture was the highest one (1559 °C), which was relatively close to the calculated adiabatic temperature (1930 °C). The addition of a small amount of flux, such as H3BO3, enabled the formation of pure α-SrAl2O4 directly from the combustion reaction.

CRAFT (complete reduction to amplitude frequency table)--robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR.

PubMed

Krishnamurthy, Krish

2013-12-01

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR-based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time-domain Bayesian approaches have been reported to be better than conventional frequency-domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time-efficient fashion - thus converting the time-domain FID to a frequency-amplitude table. CRAFT uses a two-step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

Factorial Design Approach in Proportioning Prestressed Self-Compacting Concrete.

PubMed

Long, Wu-Jian; Khayat, Kamal Henri; Lemieux, Guillaume; Xing, Feng; Wang, Wei-Lun

2015-03-13

In order to model the effect of mixture parameters and material properties on the hardened properties of, prestressed self-compacting concrete (SCC), and also to investigate the extensions of the statistical models, a factorial design was employed to identify the relative significance of these primary parameters and their interactions in terms of the mechanical and visco-elastic properties of SCC. In addition to the 16 fractional factorial mixtures evaluated in the modeled region of -1 to +1, eight axial mixtures were prepared at extreme values of -2 and +2 with the other variables maintained at the central points. Four replicate central mixtures were also evaluated. The effects of five mixture parameters, including binder type, binder content, dosage of viscosity-modifying admixture (VMA), water-cementitious material ratio (w/cm), and sand-to-total aggregate ratio (S/A) on compressive strength, modulus of elasticity, as well as autogenous and drying shrinkage are discussed. The applications of the models to better understand trade-offs between mixture parameters and carry out comparisons among various responses are also highlighted. A logical design approach would be to use the existing model to predict the optimal design, and then run selected tests to quantify the influence of the new binder on the model.

Rapid Characterization of Microalgae and Microalgae Mixtures Using Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS)

PubMed Central

Barbano, Duane; Diaz, Regina; Zhang, Lin; Sandrin, Todd; Gerken, Henri; Dempster, Thomas

2015-01-01

Current molecular methods to characterize microalgae are time-intensive and expensive. Matrix Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) may represent a rapid and economical alternative approach. The objectives of this study were to determine whether MALDI-TOF MS can be used to: 1) differentiate microalgae at the species and strain levels and 2) characterize simple microalgal mixtures. A common protein extraction sample preparation method was used to facilitate rapid mass spectrometry-based analysis of 31 microalgae. Each yielded spectra containing between 6 and 56 peaks in the m/z 2,000 to 20,000 range. The taxonomic resolution of this approach appeared higher than that of 18S rDNA sequence analysis. For example, two strains of Scenedesmus acutus differed only by two 18S rDNA nucleotides, but yielded distinct MALDI-TOF mass spectra. Mixtures of two and three microalgae yielded relatively complex spectra that contained peaks associated with members of each mixture. Interestingly, though, mixture-specific peaks were observed at m/z 11,048 and 11,230. Our results suggest that MALDI-TOF MS affords rapid characterization of individual microalgae and simple microalgal mixtures. PMID:26271045

Novel associations between contaminant body burdens and biomarkers of reproductive condition in male Common Carp along multiple gradients of contaminant exposure in Lake Mead National Recreation Area, USA

USGS Publications Warehouse

Patino, Reynaldo; VanLandeghem, Matthew M.; Goodbred, Steven L.; Orsak, Erik; Jenkins, Jill A.; Echols, Kathy R.; Rosen, Michael R.; Torres, Leticia

2015-01-01

Adult male Common Carp were sampled in 2007/08 over a full reproductive cycle at Lake Mead National Recreation Area. Sites sampled included a stream dominated by treated wastewater effluent, a lake basin receiving the streamflow, an upstream lake basin (reference), and a site below Hoover Dam. Individual body burdens for 252 contaminants were measured, and biological variables assessed included physiological [plasma vitellogenin (VTG), estradiol-17β (E2), 11-ketotestosterone (11KT)] and organ [gonadosomatic index (GSI)] endpoints. Patterns in contaminant composition and biological condition were determined by Principal Component Analysis, and their associations modeled by Principal Component Regression. Three spatially distinct but temporally stable gradients of contaminant distribution were recognized: a contaminant mixture typical of wastewaters (PBDEs, methyl triclosan, galaxolide), PCBs, and DDTs. Two spatiotemporally variable patterns of biological condition were recognized: a primary pattern consisting of reproductive condition variables (11KT, E2, GSI), and a secondary pattern including general condition traits (condition factor, hematocrit, fork length). VTG was low in all fish, indicating low estrogenic activity of water at all sites. Wastewater contaminants associated negatively with GSI, 11KT and E2; PCBs associated negatively with GSI and 11KT; and DDTs associated positively with GSI and 11KT. Regression of GSI on sex steroids revealed a novel, nonlinear association between these variables. Inclusion of sex steroids in the GSI regression on contaminants rendered wastewater contaminants nonsignificant in the model and reduced the influence of PCBs and DDTs. Thus, the influence of contaminants on GSI may have been partially driven by organismal modes-of-action that include changes in sex steroid production. The positive association of DDTs with 11KT and GSI suggests that lifetime, sub-lethal exposures to DDTs have effects on male carp opposite of those reported by studies where exposure concentrations were relatively high. Lastly, this study highlighted advantages of multivariate/multiple regression approaches for exploring associations between complex contaminant mixtures and gradients and reproductive condition in wild fishes.

Novel associations between contaminant body burdens and biomarkers of reproductive condition in male Common Carp along multiple gradients of contaminant exposure in Lake Mead National Recreation Area, USA.

PubMed

Patiño, Reynaldo; VanLandeghem, Matthew M; Goodbred, Steven L; Orsak, Erik; Jenkins, Jill A; Echols, Kathy; Rosen, Michael R; Torres, Leticia

2015-08-01

Adult male Common Carp were sampled in 2007/08 over a full reproductive cycle at Lake Mead National Recreation Area. Sites sampled included a stream dominated by treated wastewater effluent, a lake basin receiving the streamflow, an upstream lake basin (reference), and a site below Hoover Dam. Individual body burdens for 252 contaminants were measured, and biological variables assessed included physiological [plasma vitellogenin (VTG), estradiol-17β (E2), 11-ketotestosterone (11KT)] and organ [gonadosomatic index (GSI)] endpoints. Patterns in contaminant composition and biological condition were determined by Principal Component Analysis, and their associations modeled by Principal Component Regression. Three spatially distinct but temporally stable gradients of contaminant distribution were recognized: a contaminant mixture typical of wastewaters (PBDEs, methyl triclosan, galaxolide), PCBs, and DDTs. Two spatiotemporally variable patterns of biological condition were recognized: a primary pattern consisting of reproductive condition variables (11KT, E2, GSI), and a secondary pattern including general condition traits (condition factor, hematocrit, fork length). VTG was low in all fish, indicating low estrogenic activity of water at all sites. Wastewater contaminants associated negatively with GSI, 11KT and E2; PCBs associated negatively with GSI and 11KT; and DDTs associated positively with GSI and 11KT. Regression of GSI on sex steroids revealed a novel, nonlinear association between these variables. Inclusion of sex steroids in the GSI regression on contaminants rendered wastewater contaminants nonsignificant in the model and reduced the influence of PCBs and DDTs. Thus, the influence of contaminants on GSI may have been partially driven by organismal modes-of-action that include changes in sex steroid production. The positive association of DDTs with 11KT and GSI suggests that lifetime, sub-lethal exposures to DDTs have effects on male carp opposite of those reported by studies where exposure concentrations were relatively high. Lastly, this study highlighted advantages of multivariate/multiple regression approaches for exploring associations between complex contaminant mixtures and gradients and reproductive condition in wild fishes. Published by Elsevier Inc.

Pattern Recognition Algorithm for High-Sensitivity Odorant Detection in Unknown Environments

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2012-01-01

In a realistic odorant detection application environment, the collected sensory data is a mix of unknown chemicals with unknown concentrations and noise. The identification of the odorants among these mixtures is a challenge in data recognition. In addition, deriving their individual concentrations in the mix is also a challenge. A deterministic analytical model was developed to accurately identify odorants and calculate their concentrations in a mixture with noisy data.

Separation processes using expulsion from dilute supercritical solutions

DOEpatents

Cochran, H.D. Jr.

1993-04-20

A process is described for separating isotopes as well as other mixtures by utilizing the behavior of dilute repulsive or weakly attractive elements of the mixtures as the critical point of the solvent is approached.

Graphical Evaluation of the Ridge-Type Robust Regression Estimators in Mixture Experiments

PubMed Central

Erkoc, Ali; Emiroglu, Esra

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set. PMID:25202738

Graphical evaluation of the ridge-type robust regression estimators in mixture experiments.

PubMed

Erkoc, Ali; Emiroglu, Esra; Akay, Kadri Ulas

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set.

Additive and synergistic antiandrogenic activities of mixtures of azol fungicides and vinclozolin.

PubMed

Christen, Verena; Crettaz, Pierre; Fent, Karl

2014-09-15

Many pesticides including pyrethroids and azole fungicides are suspected to have an endocrine disrupting property. At present, the joint activity of compound mixtures is only marginally known. Here we tested the hypothesis that the antiandrogenic activity of mixtures of azole fungicides can be predicted by the concentration addition (CA) model. The antiandrogenic activity was assessed in MDA-kb2 cells. Following assessing single compounds activities mixtures of azole fungicides and vinclozolin were investigated. Interactions were analyzed by direct comparison between experimental and estimated dose-response curves assuming CA, followed by an analysis by the isobole method and the toxic unit approach. The antiandrogenic activity of pyrethroids deltamethrin, cypermethrin, fenvalerate and permethrin was weak, while the azole fungicides tebuconazole, propiconazole, epoxiconazole, econazole and vinclozolin exhibited strong antiandrogenic activity. Ten binary and one ternary mixture combinations of five antiandrogenic fungicides were assessed at equi-effective concentrations of EC25 and EC50. Isoboles indicated that about 50% of the binary mixtures were additive and 50% synergistic. Synergism was even more frequently indicated by the toxic unit approach. Our data lead to the conclusion that interactions in mixtures follow the CA model. However, a surprisingly high percentage of synergistic interactions occurred. Therefore, the mixture activity of antiandrogenic azole fungicides is at least additive. Mixtures should also be considered for additive antiandrogenic activity in hazard and risk assessment. Our evaluation provides an appropriate "proof of concept", but whether it equally translates to in vivo effects should further be investigated. Copyright © 2014 Elsevier Inc. All rights reserved.

Additive and synergistic antiandrogenic activities of mixtures of azol fungicides and vinclozolin

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

Christen, Verena; Crettaz, Pierre; Fent, Karl, E-mail: karl.fent@fhnw.ch

Objective: Many pesticides including pyrethroids and azole fungicides are suspected to have an endocrine disrupting property. At present, the joint activity of compound mixtures is only marginally known. Here we tested the hypothesis that the antiandrogenic activity of mixtures of azole fungicides can be predicted by the concentration addition (CA) model. Methods: The antiandrogenic activity was assessed in MDA-kb2 cells. Following assessing single compounds activities mixtures of azole fungicides and vinclozolin were investigated. Interactions were analyzed by direct comparison between experimental and estimated dose–response curves assuming CA, followed by an analysis by the isobole method and the toxic unit approach.more » Results: The antiandrogenic activity of pyrethroids deltamethrin, cypermethrin, fenvalerate and permethrin was weak, while the azole fungicides tebuconazole, propiconazole, epoxiconazole, econazole and vinclozolin exhibited strong antiandrogenic activity. Ten binary and one ternary mixture combinations of five antiandrogenic fungicides were assessed at equi-effective concentrations of EC{sub 25} and EC{sub 50}. Isoboles indicated that about 50% of the binary mixtures were additive and 50% synergistic. Synergism was even more frequently indicated by the toxic unit approach. Conclusion: Our data lead to the conclusion that interactions in mixtures follow the CA model. However, a surprisingly high percentage of synergistic interactions occurred. Therefore, the mixture activity of antiandrogenic azole fungicides is at least additive. Practice: Mixtures should also be considered for additive antiandrogenic activity in hazard and risk assessment. Implications: Our evaluation provides an appropriate “proof of concept”, but whether it equally translates to in vivo effects should further be investigated. - Highlights: • Humans are exposed to pesticide mixtures such as pyrethroids and azole fungicides. • We assessed the antiandrogenicity of pyrethroids and azole fungizides. • Many azole fungicides showed significant antiandrogenic activity . • Many binary mixtures of antiandrogenic azole fungicides showed synergistic interactions. • Concentration addition of pesticides in mixtures should be considered.« less

An odorant congruent with a colour cue is selectively perceived in an odour mixture.

PubMed

Arao, Mari; Suzuki, Maya; Katayama, Jun'ich; Akihiro, Yagi

2012-01-01

Odour identification can be influenced by colour cues. This study examined the mechanism underlying this colour context effect. We hypothesised that a specific odour component congruent with a colour would be selectively perceived in preference to another odour component in a binary odour mixture. We used a ratio estimation method under two colour conditions, a binary odour mixture (experiment 1) and single chemicals presented individually (experiment 2). Each colour was congruent with one of the odour components. Participants judged the perceived mixture ratio in each odour container on which a colour patch was pasted. An influence of colour was not observed when the odour stimulus did not contain the odour component congruent with the colour (experiment 2); however, the odour component congruent with the colour was perceived as more dominant when the odour stimulus did contain the colour-congruent odorant (experiment 1). This pattern indicates that a colour-congruent odour component is selectively perceived in an odour mixture. This finding suggests that colours can enhance the perceptual representation of the colour-associated component in an odour mixture.

Determination of solvents permeating through chemical protective clothing with a microsensor array.

PubMed

Park, J; Zellers, E T

2000-08-01

The performance of a novel prototype instrument in determining solvents and solvent mixtures permeating through samples of chemical protective clothing (CPC) materials was evaluated. The instrument contains a mini-preconcentrator and an array of three polymer-coated surface-acoustic-wave (SAW) microsensors whose collective response patterns are used to discriminate among multiple permeants. Permeation tests were performed with a 2.54 cm diameter test cell in an open-loop configuration on samples of common glove materials challenged with four individual solvents, three binary mixtures, and two ternary mixtures. Breakthrough times, defined as the times required for the permeation rate to reach a value of 1 microg cm(-2) min(-1), determined by the instrument were within 3 min of those determined in parallel by manual sampling and gas chromatographic analysis. Permeating solvents were recognized (identified) from their response patterns in 59 out of 64 measurements (92%) and their vapor concentrations were quantified to an accuracy of +/- 31% (typically +/- 10%). These results demonstrate the potential for such instrumentation to provide semi-automated field or bench-top screening of CPC permeation resistance.

Nano- and Micro-Scale Oxidative Patterning of Titanium Implant Surfaces for Improved Surface Wettability.

PubMed

Kim, In-hye; Son, Jun Sik; Choi, Seok Hwa; Kim, Kyo-han; Kwon, Tae-yub

2016-02-01

A simple and scalable surface modification treatment is demonstrated, in which nano- and microscale features are introduced into the surface of titanium (Ti) substrates by means of a novel and eco-friendly oxidative aqueous solution composed of hydrogen peroxide (H202) and sodium bicarbonate (NaHCO3). By immersing mirror-polished Ti discs in an aqueous mixture of 30 wt% H2O2/5 wt% NaHCO3 at 23 +/- 3 degrees C for 4 h, it was confirmed that this mixture is capable of generating microscale topographies on Ti surfaces. It also simultaneously formed nanochannels that were regularly arranged in a comb-like pattern on the Ti surface, thus forming a hierarchical surface structure. Further, these nano/micro-textured Ti surfaces showed great surface roughness and excellent wettability when compared with control Ti surfaces. This study demonstrates that a H2O2/NaHCO3 mixture can be effectively utilized to create reproducible nano/microscale topographies on Ti implant surfaces, thus providing an economical new oxidative solution that may be used effectively and safely as a Ti surface modification treatment.

Optimum Tolerance Design Using Component-Amount and Mixture-Amount Experiments

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

Piepel, Gregory F.; Ozler, Cenk; Sehirlioglu, Ali Kemal

2013-08-01

One type of tolerance design problem involves optimizing component and assembly tolerances to minimize the total cost (sum of manufacturing cost and quality loss). Previous literature recommended using traditional response surface (RS) designs and models to solve this type of tolerance design problem. In this article, component-amount (CA) and mixture-amount (MA) approaches are proposed as more appropriate for solving this type of tolerance design problem. The advantages of the CA and MA approaches over the RS approach are discussed. Reasons for choosing between the CA and MA approaches are also discussed. The CA and MA approaches (experimental design, response modeling,more » and optimization) are illustrated using real examples.« less

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.

Mixture models for detecting differentially expressed genes in microarrays.

PubMed

Jones, Liat Ben-Tovim; Bean, Richard; McLachlan, Geoffrey J; Zhu, Justin Xi

2006-10-01

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

Patterns of Change in Children's Loneliness: Trajectories from Third through Fifth Grades

ERIC Educational Resources Information Center

Jobe-Shields, Lisa; Cohen, Robert; Parra, Gilbert R.

2011-01-01

Latent growth-mixture modeling was used to investigate patterns of change in loneliness for 170 children from third through fifth grades. A three-class model representing unique trajectories of loneliness provided the best overall fit to the data, including a Stable Low group (65%), as well as groups of Increasers (23%) and Decreasers (12%).…

Prediction of the properties anhydrite construction mixtures based on neural network approach

NASA Astrophysics Data System (ADS)

Fedorchuk, Y. M.; Zamyatin, N. V.; Smirnov, G. V.; Rusina, O. N.; Sadenova, M. A.

2017-08-01

The article considered the question of applying the backstop modeling mechanism from the components of anhydride mixtures in the process of managing the technological processes of receiving construction products which based on fluoranhydrite.

Application of four anti-human interferon-alpha monoclonal antibodies for immunoassay and comparative analysis of natural interferon-alpha mixtures

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

Andersson, G.; Lundgren, E.; Ekre, H.P.

Four different mouse monoclonal antibodies to human interferon-alpha (IFN-alpha) were evaluated for application in quantitative and comparative analysis of natural IFN-alpha mixtures. Binding to IFN-alpha subtypes in solution revealed individual reactivity patterns. These patterns changed if the IFN-alpha molecules were immobilized either passively to a surface or bound by another antibody. Also, substitution of a single amino acid in IFN-alpha 2 affected the binding, apparently by altering the conformation. Isoelectric focusing of three natural IFN-alpha preparations from different sources, followed by immunoblotting, resulted in individual patterns with each of the four mAbs and also demonstrated variation in the composition ofmore » the IFN-alpha preparations. None of the mAbs was subtype specific, but by combining the different mAbs, and also applying polyclonal anti-human IFN-alpha antibodies, it was possible to design sensitive sandwich ELISAs with broad or more limited IFN-alpha subtype specificity.« less

Taste Mixture Interactions: Suppression, Additivity, and the Predominance of Sweetness

PubMed Central

Green, Barry G.; Lim, Juyun; Osterhoff, Floor; Blacher, Karen; Nachtigal, Danielle

2010-01-01

Most of what is known about taste interactions has come from studies of binary mixtures. The primary goal of this study was to determine whether asymmetries in suppression between stimuli in binary mixtures predict the perception of tastes in more complex mixtures (e.g., ternary, quaternary mixtures). Also of interest was the longstanding question of whether overall taste intensity derives from the sum of the tastes perceived within a mixture (perceptual additivity) or from the sum of the perceived intensities of the individual stimuli (stimulus additivity). Using the general Labeled Magnitude Scale together with a sip-and-spit procedure, we asked subjects to rate overall taste intensity and the sweetness, sourness, saltiness and bitterness of approximately equi- intense sucrose, NaCl, citric acid and QSO4 stimuli presented alone and in all possible binary, ternary and quaternary mixtures. The results showed a consistent pattern of mixture suppression in which sucrose sweetness tended to be both the least suppressed quality and the strongest suppressor of other tastes. The overall intensity of mixtures was found to be predicted best by perceptual additivity. A second experiment that was designed to rule out potentially confounding effects of the order of taste ratings and the temperature of taste solutions replicated the main findings of the first experiment. Overall, the results imply that mixture suppression favors perception of sweet carbohydrates in foods at the expense of other potentially harmful ingredients, such as high levels of sodium (saltiness) and potential poisons or spoilage (bitterness, sourness). PMID:20800076

Communication: Modeling electrolyte mixtures with concentration dependent dielectric permittivity

NASA Astrophysics Data System (ADS)

Chen, Hsieh; Panagiotopoulos, Athanassios Z.

2018-01-01

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

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,...

Innovative aspects of protein stability in ionic liquid mixtures.

PubMed

Kumar, Awanish; Venkatesu, Pannuru

2018-06-01

Mixtures of ionic liquids (ILs) have attracted our attention because of their extraordinary performances in extraction technologies and in absorbing large amount of CO 2 gas. It has been observed that when two or more ILs are mixed in different proportions, a new solvent is obtained which is much better than that of each component of ILs from which the mixture is obtained. Within a mixture of ILs, several unidentified interactions occur among several ions which give rise to unique solvent properties to the mixture. Herein, in this review, we have highlighted the utilization of the advantageous properties of the IL mixtures in protein stability studies. This approach is exceptional and opens new directions to the use of ILs in biotechnology.

An Approach for Peptide Identification by De Novo Sequencing of Mixture Spectra.

PubMed

Liu, Yi; Ma, Bin; Zhang, Kaizhong; Lajoie, Gilles

2017-01-01

Mixture spectra occur quite frequently in a typical wet-lab mass spectrometry experiment, which result from the concurrent fragmentation of multiple precursors. The ability to efficiently and confidently identify mixture spectra is essential to alleviate the existent bottleneck of low mass spectra identification rate. However, most of the traditional computational methods are not suitable for interpreting mixture spectra, because they still take the assumption that the acquired spectra come from the fragmentation of a single precursor. In this manuscript, we formulate the mixture spectra de novo sequencing problem mathematically, and propose a dynamic programming algorithm for the problem. Additionally, we use both simulated and real mixture spectra data sets to verify the merits of the proposed algorithm.

The Association of Levels of and Decline in Grip Strength in Old Age with Trajectories of Life Course Occupational Position.

PubMed

Kröger, Hannes; Fritzell, Johan; Hoffmann, Rasmus

2016-01-01

The study of the influence of life course occupational position (OP) on health in old age demands analysis of time patterns in both OP and health. We study associations between life course time patterns of OP and decline in grip strength in old age. We analyze 5 waves from the Survey of Health Ageing and Retirement in Europe (n = 5108, ages 65-90). We use a pattern-mixture latent growth model to predict the level and decline in grip strength in old age by trajectory of life course OP. We extend and generalize the structured regression approach to establish the explanatory power of different life course models for both the level and decline of grip strength. Grip strength declined linearly by 0.70 kg (95% CI -0.74;-0.66) for men and 0.42 kg (95% CI -0.45;-0.39) for women per year. The level of men's grip strength can best be explained by a critical period during midlife, with those exposed to low OP during this period having 1.67 kg (95% CI -2.33;-1.00) less grip strength. These differences remain constant over age. For women, no association between OP and levels of or decline in grip strength was found. Men's OP in midlife seems to be a critical period for the level of grip strength in old age. Inequalities remain constant over age. The integration of the structured regression approach and latent growth modelling offers new possibilities for life course epidemiology.

Original predictive approach to the compressibility of pharmaceutical powder mixtures based on the Kawakita equation.

PubMed

Mazel, Vincent; Busignies, Virginie; Duca, Stéphane; Leclerc, Bernard; Tchoreloff, Pierre

2011-05-30

In the pharmaceutical industry, tablets are obtained by the compaction of two or more components which have different physical properties and compaction behaviours. Therefore, it could be interesting to predict the physical properties of the mixture using the single-component results. In this paper, we have focused on the prediction of the compressibility of binary mixtures using the Kawakita model. Microcrystalline cellulose (MCC) and L-alanine were compacted alone and mixed at different weight fractions. The volume reduction, as a function of the compaction pressure, was acquired during the compaction process ("in-die") and after elastic recovery ("out-of-die"). For the pure components, the Kawakita model is well suited to the description of the volume reduction. For binary mixtures, an original approach for the prediction of the volume reduction without using the effective Kawakita parameters was proposed and tested. The good agreement between experimental and predicted data proved that this model was efficient to predict the volume reduction of MCC and L-alanine mixtures during compaction experiments. Copyright © 2011 Elsevier B.V. All rights reserved.

Molecular identification of organic compounds in atmospheric complex mixtures and relationship to atmospheric chemistry and sources.

PubMed

Mazurek, Monica A

2002-12-01

This article describes a chemical characterization approach for complex organic compound mixtures associated with fine atmospheric particles of diameters less than 2.5 m (PM2.5). It relates molecular- and bulk-level chemical characteristics of the complex mixture to atmospheric chemistry and to emission sources. Overall, the analytical approach describes the organic complex mixtures in terms of a chemical mass balance (CMB). Here, the complex mixture is related to a bulk elemental measurement (total carbon) and is broken down systematically into functional groups and molecular compositions. The CMB and molecular-level information can be used to understand the sources of the atmospheric fine particles through conversion of chromatographic data and by incorporation into receptor-based CMB models. Once described and quantified within a mass balance framework, the chemical profiles for aerosol organic matter can be applied to existing air quality issues. Examples include understanding health effects of PM2.5 and defining and controlling key sources of anthropogenic fine particles. Overall, the organic aerosol compositional data provide chemical information needed for effective PM2.5 management.

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.

Experimental designs and risk assessment in combination toxicology: panel discussion.

PubMed

Henschler, D; Bolt, H M; Jonker, D; Pieters, M N; Groten, J P

1996-01-01

Advancing our knowledge on the toxicology of combined exposures to chemicals and implementation of this knowledge in guidelines for health risk assessment of such combined exposures are necessities dictated by the simple fact that humans are continuously exposed to a multitude of chemicals. A prerequisite for successful research and fruitful discussions on the toxicology of combined exposures (mixtures of chemicals) is the use of defined terminology implemented by an authoritative international body such as, for example, the International Union of Pure and Applied Chemistry (IUPAC) Toxicology Committee. The extreme complexity of mixture toxicology calls for new research methodologies to study interactive effects, taking into account limited resources. Of these methodologies, statistical designs and mathematical modelling of toxicokinetics and toxicodynamics seem to be most promising. Emphasis should be placed on low-dose modelling and experimental validation. The scientifically sound so-called bottom-up approach should be supplemented with more pragmatic approaches, focusing on selection of the most hazardous chemicals in a mixture and careful consideration of the mode of action and possible interactive effects of these chemicals. Pragmatic approaches may be of particular importance to study and evaluate complex mixtures; after identification of the 'top ten' (most risky) chemicals in the mixture they can be examined and evaluated as a defined (simple) chemical mixture. In setting exposure limits for individual chemicals, the use of an additional safety factor to compensate for potential increased risk due to simultaneous exposure to other chemicals, has no clear scientific justification. The use of such an additional factor is a political rather than a scientific choice.

Three-dimensional convection of binary mixtures in porous media.

PubMed

Umla, R; Augustin, M; Huke, B; Lücke, M

2011-11-01

We investigate convection patterns of binary mixtures with a positive separation ratio in porous media. As setup, we choose the Rayleigh-Bénard system of a fluid layer heated from below. Results are obtained by a multimode Galerkin method. Using this method, we compute square and crossroll patterns, and we analyze their structural, bifurcation, and stability properties. Evidence is provided that, for a strong enough Soret effect, both structures exist as stable forms of convection. Some of their properties are found to be similar to square and crossroll convection in the system without porous medium. However, there are also qualitative differences. For example, squares can be destabilized by oscillatory perturbations with square symmetry in porous media, and their velocity isolines are deformed in the so-called Soret regime.

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

Quantifying Short-Chain Chlorinated Paraffin Congener Groups.

PubMed

Yuan, Bo; Bogdal, Christian; Berger, Urs; MacLeod, Matthew; Gebbink, Wouter A; Alsberg, Tomas; de Wit, Cynthia A

2017-09-19

Accurate quantification of short-chain chlorinated paraffins (SCCPs) poses an exceptional challenge to analytical chemists. SCCPs are complex mixtures of chlorinated alkanes with variable chain length and chlorination level; congeners with a fixed chain length (n) and number of chlorines (m) are referred to as a "congener group" C n Cl m . Recently, we resolved individual C n Cl m by mathematically deconvolving soft ionization high-resolution mass spectra of SCCP mixtures. Here we extend the method to quantifying C n Cl m by introducing C n Cl m specific response factors (RFs) that are calculated from 17 SCCP chain-length standards with a single carbon chain length and variable chlorination level. The signal pattern of each standard is measured on APCI-QTOF-MS. RFs of each C n Cl m are obtained by pairwise optimization of the normal distribution's fit to the signal patterns of the 17 chain-length standards. The method was verified by quantifying SCCP technical mixtures and spiked environmental samples with accuracies of 82-123% and 76-109%, respectively. The absolute differences between calculated and manufacturer-reported chlorination degrees were -0.9 to 1.0%Cl for SCCP mixtures of 49-71%Cl. The quantification method has been replicated with ECNI magnetic sector MS and ECNI-Q-Orbitrap-MS. C n Cl m concentrations determined with the three instruments were highly correlated (R 2 > 0.90) with each other.

Toxicity interactions between manganese (Mn) and lead (Pb) or cadmium (Cd) in a model organism the nematode C. elegans.

PubMed

Lu, Cailing; Svoboda, Kurt R; Lenz, Kade A; Pattison, Claire; Ma, Hongbo

2018-06-01

Manganese (Mn) is considered as an emerging metal contaminant in the environment. However, its potential interactions with companying toxic metals and the associated mixture effects are largely unknown. Here, we investigated the toxicity interactions between Mn and two commonly seen co-occurring toxic metals, Pb and Cd, in a model organism the nematode Caenorhabditis elegans. The acute lethal toxicity of mixtures of Mn+Pb and Mn+Cd were first assessed using a toxic unit model. Multiple toxicity endpoints including reproduction, lifespan, stress response, and neurotoxicity were then examined to evaluate the mixture effects at sublethal concentrations. Stress response was assessed using a daf-16::GFP transgenic strain that expresses GFP under the control of DAF-16 promotor. Neurotoxicity was assessed using a dat-1::GFP transgenic strain that expresses GFP in dopaminergic neurons. The mixture of Mn+Pb induced a more-than-additive (synergistic) lethal toxicity in the worm whereas the mixture of Mn+Cd induced a less-than-additive (antagonistic) toxicity. Mixture effects on sublethal toxicity showed more complex patterns and were dependent on the toxicity endpoints as well as the modes of toxic action of the metals. The mixture of Mn+Pb induced additive effects on both reproduction and lifespan, whereas the mixture of Mn+Cd induced additive effects on lifespan but not reproduction. Both mixtures seemed to induce additive effects on stress response and neurotoxicity, although a quantitative assessment was not possible due to the single concentrations used in mixture tests. Our findings demonstrate the complexity of metal interactions and the associated mixture effects. Assessment of metal mixture toxicity should take into consideration the unique property of individual metals, their potential toxicity mechanisms, and the toxicity endpoints examined.

Using Bayesian statistics for modeling PTSD through Latent Growth Mixture Modeling: implementation and discussion.

PubMed

Depaoli, Sarah; van de Schoot, Rens; van Loey, Nancy; Sijbrandij, Marit

2015-01-01

After traumatic events, such as disaster, war trauma, and injuries including burns (which is the focus here), the risk to develop posttraumatic stress disorder (PTSD) is approximately 10% (Breslau & Davis, 1992). Latent Growth Mixture Modeling can be used to classify individuals into distinct groups exhibiting different patterns of PTSD (Galatzer-Levy, 2015). Currently, empirical evidence points to four distinct trajectories of PTSD patterns in those who have experienced burn trauma. These trajectories are labeled as: resilient, recovery, chronic, and delayed onset trajectories (e.g., Bonanno, 2004; Bonanno, Brewin, Kaniasty, & Greca, 2010; Maercker, Gäbler, O'Neil, Schützwohl, & Müller, 2013; Pietrzak et al., 2013). The delayed onset trajectory affects only a small group of individuals, that is, about 4-5% (O'Donnell, Elliott, Lau, & Creamer, 2007). In addition to its low frequency, the later onset of this trajectory may contribute to the fact that these individuals can be easily overlooked by professionals. In this special symposium on Estimating PTSD trajectories (Van de Schoot, 2015a), we illustrate how to properly identify this small group of individuals through the Bayesian estimation framework using previous knowledge through priors (see, e.g., Depaoli & Boyajian, 2014; Van de Schoot, Broere, Perryck, Zondervan-Zwijnenburg, & Van Loey, 2015). We used latent growth mixture modeling (LGMM) (Van de Schoot, 2015b) to estimate PTSD trajectories across 4 years that followed a traumatic burn. We demonstrate and compare results from traditional (maximum likelihood) and Bayesian estimation using priors (see, Depaoli, 2012, 2013). Further, we discuss where priors come from and how to define them in the estimation process. We demonstrate that only the Bayesian approach results in the desired theory-driven solution of PTSD trajectories. Since the priors are chosen subjectively, we also present a sensitivity analysis of the Bayesian results to illustrate how to check the impact of the prior knowledge integrated into the model. We conclude with recommendations and guidelines for researchers looking to implement theory-driven LGMM, and we tailor this discussion to the context of PTSD research.

Critical Casimir effect for colloids close to chemically patterned substrates.

PubMed

Tröndle, M; Kondrat, S; Gambassi, A; Harnau, L; Dietrich, S

2010-08-21

Colloids immersed in a critical or near-critical binary liquid mixture and close to a chemically patterned substrate are subject to normal and lateral critical Casimir forces of dominating strength. For a single colloid, we calculate these attractive or repulsive forces and the corresponding critical Casimir potentials within mean-field theory. Within this approach we also discuss the quality of the Derjaguin approximation and apply it to Monte Carlo simulation data available for the system under study. We find that the range of validity of the Derjaguin approximation is rather large and that it fails only for surface structures which are very small compared to the geometric mean of the size of the colloid and its distance from the substrate. For certain chemical structures of the substrate, the critical Casimir force acting on the colloid can change sign as a function of the distance between the particle and the substrate; this provides a mechanism for stable levitation at a certain distance which can be strongly tuned by temperature, i.e., with a sensitivity of more than 200 nm/K.

Simultaneous Synchrotron WAXD and Fast Scanning (Chip) Calorimetry: On the (Isothermal) Crystallization of HDPE and PA11 at High Supercoolings and Cooling Rates up to 200 °C s(-1).

PubMed

Baeten, Dorien; Mathot, Vincent B F; Pijpers, Thijs F J; Verkinderen, Olivier; Portale, Giuseppe; Van Puyvelde, Peter; Goderis, Bart

2015-06-01

An experimental setup, making use of a Flash DSC 1 prototype, is presented in which materials can be studied simultaneously by fast scanning calorimetry (FSC) and synchrotron wide angle X-ray diffraction (WAXD). Accumulation of multiple, identical measurements results in high quality, millisecond WAXD patterns. Patterns at every degree during the crystallization and melting of high density polyethylene at FSC typical scanning rates from 20 up to 200 °C s(-1) are discussed in terms of the temperature and scanning rate dependent material crystallinities and crystal densities. Interestingly, the combined approach reveals FSC thermal lag issues, for which can be corrected. For polyamide 11, isothermal solidification at high supercooling yields a mesomorphic phase in less than a second, whereas at very low supercooling crystals are obtained. At intermediate supercooling, mixtures of mesomorphic and crystalline material are generated at a ratio proportional to the supercooling. This ratio is constant over the isothermal solidification time. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On an interface of the online system for a stochastic analysis of the varied information flows

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

Gorshenin, Andrey K.; MIREA, MGUPI; Kuzmin, Victor Yu.

The article describes a possible approach to the construction of an interface of an online asynchronous system that allows researchers to analyse varied information flows. The implemented stochastic methods are based on the mixture models and the method of moving separation of mixtures. The general ideas of the system functionality are demonstrated on an example for some moments of a finite normal mixture.

Factorial Design Approach in Proportioning Prestressed Self-Compacting Concrete

PubMed Central

Long, Wu-Jian; Khayat, Kamal Henri; Lemieux, Guillaume; Xing, Feng; Wang, Wei-Lun

2015-01-01

In order to model the effect of mixture parameters and material properties on the hardened properties of, prestressed self-compacting concrete (SCC), and also to investigate the extensions of the statistical models, a factorial design was employed to identify the relative significance of these primary parameters and their interactions in terms of the mechanical and visco-elastic properties of SCC. In addition to the 16 fractional factorial mixtures evaluated in the modeled region of −1 to +1, eight axial mixtures were prepared at extreme values of −2 and +2 with the other variables maintained at the central points. Four replicate central mixtures were also evaluated. The effects of five mixture parameters, including binder type, binder content, dosage of viscosity-modifying admixture (VMA), water-cementitious material ratio (w/cm), and sand-to-total aggregate ratio (S/A) on compressive strength, modulus of elasticity, as well as autogenous and drying shrinkage are discussed. The applications of the models to better understand trade-offs between mixture parameters and carry out comparisons among various responses are also highlighted. A logical design approach would be to use the existing model to predict the optimal design, and then run selected tests to quantify the influence of the new binder on the model. PMID:28787990

Test of cold asphalt storability based on alternative approaches

NASA Astrophysics Data System (ADS)

Abaffyová, Zora; Komačka, Jozef

2017-09-01

Cold asphalt products for potholes repairs should be workable (soft enough) for long time to ensure their applicability. Storability is assessed indirectly using various tests of workability. Therefore, simple test methods (self-compaction and disintegration test) was developed and verified to investigate changes of storability of this group of cold asphalts. Selfcompaction of the tested mixture in the upturned Abram’s cone for the cement concrete slump test and in the mould for the California Bearing Ratio test was assessed in first stage. After that the video record of disintegration test was taken. During this test, the mould was lifted up and the mixture fell off the mould (Abram’s cone) or disintegrate (CBR mould). The drop of surface after 10 min self-compaction and netto time related to falling out or disintegration of the mixture were used to evaluate the mixture from storability point of view. It was found out the self-compaction test has not a potential to reveal and prove changes of mixture properties. Based on the disintegration test results it can be stated this test at 5 °C using the upturned Abram’s cone could be a suitable approach to determine qualitative changes of a cold mixture from storability point of view.

Isotopic characteristics of simulated meteoritic organic matter. I - Kerogen-like material

NASA Technical Reports Server (NTRS)

Kerridge, John F.; Mariner, Ruth; Flores, Jose; Chang, Sherwood

1989-01-01

Carbonaceous residues from a variety of laboratory syntheses yield release patterns for C and H isotopes during stepwise combustion that fail to mimic the striking patterns characteristic of meteoritic kerogen-like residues that otherwise superficially resemble them. It seems likely that the meteoritic material comprises a complex mixture of substances having different origins and/or synthesis conditions.

ZEP520A cold-development technique and tool for ultimate resolution to fabricate 1Xnm bit pattern EB master mold for nano-imprinting lithography for HDD/BPM development

NASA Astrophysics Data System (ADS)

Kobayashi, Hideo; Iyama, Hiromasa

2012-06-01

Poor solvent developers are effective for resolution enhancement on a polymer-type EB resist such as ZEP520A. Another way is to utilize "cold-development" technique which was accomplished by a dip-development technique usually. We then designed and successfully built a single-wafer spin-development tool for the cold-development down to -10degC in order to dissolve difficulties of the dip-development. The cold-development certainly helped improve ZEP520A resolution and hole CD size uniformity, and achieved 35nm pitch BPM patterns with the standard developer ZED-N50, but not 25nm pitch yet. By employing a poor solvent mixture of iso-Propyl Alcohol (IPA) and Fluoro-Carbon (FC), 25nm pitch BPM patterns were accomplished. However, the cold-development showed almost no improvement on the IPA/FC mixture developer solvent. This paper describes cold-development technique and a tool, as well as its results, for ZEP520A resolution enhancement to fabricate 1Xnm bits (holes) for EB master-mold for Nano-Imprinting Lithography for 1Tbit/inch2 and 25nm pitch Bit Patterned Media development.

Odor Perception by Dogs: Evaluating Two Training Approaches for Odor Learning of Sniffer Dogs.

PubMed

Fischer-Tenhagen, Carola; Johnen, Dorothea; Heuwieser, Wolfgang; Becker, Roland; Schallschmidt, Kristin; Nehls, Irene

2017-06-01

In this study, a standardized experimental set-up with various combinations of herbs as odor sources was designed. Two training approaches for sniffer dogs were compared; first, training with a pure reference odor, and second, training with a variety of odor mixtures with the target odor as a common denominator. The ability of the dogs to identify the target odor in a new context was tested. Six different herbs (basil, St. John's wort, dandelion, marjoram, parsley, ribwort) were chosen to produce reference materials in various mixtures with (positive) and without (negative) chamomile as the target odor source. The dogs were trained to show 1 of 2 different behaviors, 1 for the positive, and 1 for the negative sample as a yes/no task. Tests were double blind with one sample presented at a time. In both training approaches, dogs were able to detect chamomile as the target odor in any presented mixture with an average sensitivity of 72% and a specificity of 84%. Dogs trained with odor mixture containing the target odor had more correct indications in the transfer task. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Assessment of the Risks of Mixtures of Major Use Veterinary Antibiotics in European Surface Waters.

PubMed

Guo, Jiahua; Selby, Katherine; Boxall, Alistair B A

2016-08-02

Effects of single veterinary antibiotics on a range of aquatic organisms have been explored in many studies. In reality, surface waters will be exposed to mixtures of these substances. In this study, we present an approach for establishing risks of antibiotic mixtures to surface waters and illustrate this by assessing risks of mixtures of three major use antibiotics (trimethoprim, tylosin, and lincomycin) to algal and cyanobacterial species in European surface waters. Ecotoxicity tests were initially performed to assess the combined effects of the antibiotics to the cyanobacteria Anabaena flos-aquae. The results were used to evaluate two mixture prediction models: concentration addition (CA) and independent action (IA). The CA model performed best at predicting the toxicity of the mixture with the experimental 96 h EC50 for the antibiotic mixture being 0.248 μmol/L compared to the CA predicted EC50 of 0.21 μmol/L. The CA model was therefore used alongside predictions of exposure for different European scenarios and estimations of hazards obtained from species sensitivity distributions to estimate risks of mixtures of the three antibiotics. Risk quotients for the different scenarios ranged from 0.066 to 385 indicating that the combination of three substances could be causing adverse impacts on algal communities in European surface waters. This could have important implications for primary production and nutrient cycling. Tylosin contributed most to the risk followed by lincomycin and trimethoprim. While we have explored only three antibiotics, the combined experimental and modeling approach could readily be applied to the wider range of antibiotics that are in use.

Phase behaviour of the symmetric binary mixture from thermodynamic perturbation theory.

PubMed

Dorsaz, N; Foffi, G

2010-03-17

We study the phase behaviour of symmetric binary mixtures of hard core Yukawa (HCY) particles via thermodynamic perturbation theory (TPT). We show that all the topologies of phase diagram reported for the symmetric binary mixtures are correctly reproduced within the TPT approach. In a second step we use the capability of TPT to be straightforwardly extended to mixtures that are nonsymmetric in size. Starting from mixtures that belong to the different topologies of symmetric binary mixtures we investigate the effect on the phase behaviour when an asymmetry in the diameters of the two components is introduced. Interestingly, when the energy of interaction between unlike particles is weaker than the interaction between like particles, the propensity for the solution to demix is found to increase strongly with size asymmetry.

A Bayesian Joint Model of Menstrual Cycle Length and Fecundity

PubMed Central

Lum, Kirsten J.; Sundaram, Rajeshwari; Louis, Germaine M. Buck; Louis, Thomas A.

2015-01-01

Summary Menstrual cycle length (MCL) has been shown to play an important role in couple fecundity, which is the biologic capacity for reproduction irrespective of pregnancy intentions. However, a comprehensive assessment of its role requires a fecundity model that accounts for male and female attributes and the couple’s intercourse pattern relative to the ovulation day. To this end, we employ a Bayesian joint model for MCL and pregnancy. MCLs follow a scale multiplied (accelerated) mixture model with Gaussian and Gumbel components; the pregnancy model includes MCL as a covariate and computes the cycle-specific probability of pregnancy in a menstrual cycle conditional on the pattern of intercourse and no previous fertilization. Day-specific fertilization probability is modeled using natural, cubic splines. We analyze data from the Longitudinal Investigation of Fertility and the Environment Study (the LIFE Study), a couple based prospective pregnancy study, and find a statistically significant quadratic relation between fecundity and menstrual cycle length, after adjustment for intercourse pattern and other attributes, including male semen quality, both partner’s age, and active smoking status (determined by baseline cotinine level 100ng/mL). We compare results to those produced by a more basic model and show the advantages of a more comprehensive approach. PMID:26295923

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.

Probabilistic n/γ discrimination with robustness against outliers for use in neutron profile monitors

NASA Astrophysics Data System (ADS)

Uchida, Y.; Takada, E.; Fujisaki, A.; Kikuchi, T.; Ogawa, K.; Isobe, M.

2017-08-01

A method to stochastically discriminate neutron and γ-ray signals measured with a stilbene organic scintillator is proposed. Each pulse signal was stochastically categorized into two groups: neutron and γ-ray. In previous work, the Expectation Maximization (EM) algorithm was used with the assumption that the measured data followed a Gaussian mixture distribution. It was shown that probabilistic discrimination between these groups is possible. Moreover, by setting the initial parameters for the Gaussian mixture distribution with a k-means algorithm, the possibility of automatic discrimination was demonstrated. In this study, the Student's t-mixture distribution was used as a probabilistic distribution with the EM algorithm to improve the robustness against the effect of outliers caused by pileup of the signals. To validate the proposed method, the figures of merit (FOMs) were compared for the EM algorithm assuming a t-mixture distribution and a Gaussian mixture distribution. The t-mixture distribution resulted in an improvement of the FOMs compared with the Gaussian mixture distribution. The proposed data processing technique is a promising tool not only for neutron and γ-ray discrimination in fusion experiments but also in other fields, for example, homeland security, cancer therapy with high energy particles, nuclear reactor decommissioning, pattern recognition, and so on.

Pattern learning with deep neural networks in EMG-based speech recognition.

PubMed

Wand, Michael; Schultz, Tanja

2014-01-01

We report on classification of phones and phonetic features from facial electromyographic (EMG) data, within the context of our EMG-based Silent Speech interface. In this paper we show that a Deep Neural Network can be used to perform this classification task, yielding a significant improvement over conventional Gaussian Mixture models. Our central contribution is the visualization of patterns which are learned by the neural network. With increasing network depth, these patterns represent more and more intricate electromyographic activity.

Use of HCA in Subproteome-immunization and Screening of Hybridoma Supernatants to Define Distinct Antibody Binding Patterns

PubMed Central

Szafran, Adam T.; Mancini, Maureen G.; Nickerson, Jeffrey A.; Edwards, Dean P.; Mancini, Michael A.

2016-01-01

Understanding the properties and functions of complex biological systems depends upon knowing the proteins present and the interactions between them. Recent advances in mass spectrometry have given us greater insights into the participating proteomes, however, monoclonal antibodies remain key to understanding the structures, functions, locations and macromolecular interactions of the involved proteins. The traditional single immunogen method to produce monoclonal antibodies using hybridoma technology are time, resource and cost intensive, limiting the number of reagents that are available. Using a high content analysis screening approach, we have developed a method in which a complex mixture of proteins (e.g., subproteome) is used to generate a panel of monoclonal antibodies specific to a subproteome located in a defined subcellular compartment such as the nucleus. The immunofluorescent images in the primary hybridoma screen are analyzed using an automated processing approach and classified using a recursive partitioning forest classification model derived from images obtained from the Human Protein Atlas. Using an ammonium sulfate purified nuclear matrix fraction as an example of reverse proteomics, we identified 866 hybridoma supernatants with a positive immunofluorescent signal. Of those, 402 produced a nuclear signal from which patterns similar to known nuclear matrix associated proteins were identified. Detailed here is our method, the analysis techniques, and a discussion of the application to further in vivo antibody production. PMID:26521976

Use of HCA in subproteome-immunization and screening of hybridoma supernatants to define distinct antibody binding patterns.

PubMed

Szafran, Adam T; Mancini, Maureen G; Nickerson, Jeffrey A; Edwards, Dean P; Mancini, Michael A

2016-03-01

Understanding the properties and functions of complex biological systems depends upon knowing the proteins present and the interactions between them. Recent advances in mass spectrometry have given us greater insights into the participating proteomes, however, monoclonal antibodies remain key to understanding the structures, functions, locations and macromolecular interactions of the involved proteins. The traditional single immunogen method to produce monoclonal antibodies using hybridoma technology are time, resource and cost intensive, limiting the number of reagents that are available. Using a high content analysis screening approach, we have developed a method in which a complex mixture of proteins (e.g., subproteome) is used to generate a panel of monoclonal antibodies specific to a subproteome located in a defined subcellular compartment such as the nucleus. The immunofluorescent images in the primary hybridoma screen are analyzed using an automated processing approach and classified using a recursive partitioning forest classification model derived from images obtained from the Human Protein Atlas. Using an ammonium sulfate purified nuclear matrix fraction as an example of reverse proteomics, we identified 866 hybridoma supernatants with a positive immunofluorescent signal. Of those, 402 produced a nuclear signal from which patterns similar to known nuclear matrix associated proteins were identified. Detailed here is our method, the analysis techniques, and a discussion of the application to further in vivo antibody production. Copyright © 2015 Elsevier Inc. All rights reserved.

Calculation of detonation initiation in a hydrogen/oxygen/argon mixture in by a small-diameter spherical projectile

NASA Astrophysics Data System (ADS)

Bedarev, I. A.; Temerbekov, V. M.; Fedorov, A. V.

2018-03-01

The initiation of detonation in a reactive mixture by a small-diameter spherical projectile launched at supersonic velocity was studied for a reduced kinetic scheme of chemical reactions. A mathematical technique based on the ANSYS Fluent package was developed for this purpose. Numerical and experimental data on the flow regimes and detonation cell sizes are compared. There is agreement between the calculated and experimental flow patterns and detonation cell sizes for each regime.

Evidence of temperature-dependent effects on the estrogenic response of fish: implications with regard to climate change.

PubMed

Brian, Jayne V; Harris, Catherine A; Runnalls, Tamsin J; Fantinati, Andrea; Pojana, Giulio; Marcomini, Antonio; Booy, Petra; Lamoree, Marja; Kortenkamp, Andreas; Sumpter, John P

2008-07-01

Chemical risk assessment is fraught with difficulty due to the problem of accounting for the effects of mixtures. In addition to the uncertainty arising from chemical-to-chemical interactions, it is possible that environmental variables, such as temperature, influence the biological response to chemical challenge, acting as confounding factors in the analysis of mixture effects. Here, we investigate the effects of temperature on the response of fish to a defined mixture of estrogenic chemicals. It was anticipated that the response to the mixture may be exacerbated at higher temperatures, due to an increase in the rate of physiological processing. This is a pertinent issue in view of global climate change. Fathead minnows (Pimephales promelas) were exposed to the mixture in parallel exposure studies, which were carried out at different temperatures (20 and 30 degrees C). The estrogenic response was characterised using an established assay, involving the analysis of the egg yolk protein, vitellogenin (VTG). Patterns of VTG gene expression were also analysed using real-time QPCR. The results revealed that there was no effect of temperature on the magnitude of the VTG response after 2 weeks of chemical exposure. However, the analysis of mixture effects at two additional time points (24 h and 7 days) revealed that the response was induced more rapidly at the higher temperature. This trend was apparent from the analysis of effects both at the molecular and biochemical level. Whilst this indicates that climatic effects on water temperature are not a significant issue with regard to the long-term risk assessment of estrogenic chemicals, the relevance of short-term effects is, as yet, unclear. Furthermore, analysis of the patterns of VTG gene expression versus protein induction gives an insight into the physiological mechanisms responsible for temperature-dependent effects on the reproductive phenology of species such as roach. Hence, the data contribute to our understanding of the implications of global climate change for wild fish populations.

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.

Bladed Terrain on Pluto: Possible Origins and Evolutions

NASA Technical Reports Server (NTRS)

Moore, Jeffrey M.; Howard, Alan D.; Umurhan, Orkan M.; White, Oliver L.; Schenk, Paul; Beyer, Ross A.; McKinnon, William B.; Spencer, John R.; Singer, Kelsi N.; Grundy, William N.;

Bladed Terrain on Pluto: Possible Origins and Evolutions

NASA Astrophysics Data System (ADS)

Moore, J. M.; Howard, A. D.; Umurhan, O. M.; White, O. L.; Schenk, P.; Beyer, R. A.; McKinnon, W. B.; Spencer, J. R.; Singer, K. N.; Grundy, W. M.; Nimmo, F.; Young, L. A.; Stern, A.; Weaver, H. A., Jr.; Olkin, C.; Ennico Smith, K.; Collins, G. C.

2016-12-01

Pluto's Bladed Terrain (centered roughly 20°N, 225°E) covers the flanks and crests of the informally named Tartarus Dorsa with numerous roughly aligned blade-like ridges oriented North-South; it may also stretch considerably farther east onto the non-close approach hemisphere but that inference is tentative. Individual ridges are typically several hundred meters high, and are spaced 5 to 10 km crest to crest, separated by V-shaped valleys. Many ridges merge at acute angles to form Y-shape junctions in plan view. The principle composition of the blades themselves we suspect is methane or a methane-rich mixture. (Methane is spectroscopically strongly observed on the optical surfaces of blades.) Nitrogen ice is very probably too soft to support their topography. Cemented mixtures of volatile and non-volatile ices may also provide a degradable but relief supporting "bedrock" for the blades, perhaps analogous to Callisto. Currently we are considering several hypotheses for the origins of the deposit from which Bladed Terrain has evolved, including aeolian disposition, atmospheric condensation, updoming and exhumation, volcanic intrusions or extrusions, crystal growth, among others. We are reviewing several processes as candidate creators or sculptors of the blades. Perhaps they are primary depositional patterns such as dunes, or differential condensation patterns (like on Callisto), or fissure extrusions. Or alternatively perhaps they are the consequence of differential erosion (such as sublimation erosion widening and deepening along cracks), variations in substrate properties, mass wasting into the subsurface, or sculpted by a combination of directional winds and solar isolation orientation. We will consider the roles of the long-term increasing solar flux and short periods of warm thick atmospheres. Hypotheses will be ordered based on observational constrains and modeling to be presented at the conference.

Estimating nanoparticle optical absorption with magnetic resonance temperature imaging and bioheat transfer simulation.

PubMed

MacLellan, Christopher J; Fuentes, David; Elliott, Andrew M; Schwartz, Jon; Hazle, John D; Stafford, R Jason

2014-02-01

Optically activated nanoparticle-mediated heating for thermal therapy applications is an area of intense research. The ability to characterise the spatio-temporal heating potential of these particles for use in modelling under various exposure conditions can aid in the exploration of new approaches for therapy as well as more quantitative prospective approaches to treatment planning. The purpose of this research was to investigate an inverse solution to the heat equation using magnetic resonance temperature imaging (MRTI) feedback, for providing optical characterisation of two types of nanoparticles (gold-silica nanoshells and gold nanorods). The optical absorption of homogeneous nanoparticle-agar mixtures was measured during exposure to an 808 nm laser using real-time MRTI. A coupled finite element solution of heat transfer was registered with the data and used to solve the inverse problem. The L2 norm of the difference between the temperature increase in the model and MRTI was minimised using a pattern search algorithm by varying the absorption coefficient of the mixture. Absorption fractions were within 10% of literature values for similar nanoparticles. Comparison of temporal and spatial profiles demonstrated good qualitative agreement between the model and the MRTI. The weighted root mean square error was <1.5 σMRTI and the average Dice similarity coefficient for ΔT = 5 °C isotherms was >0.9 over the measured time interval. This research demonstrates the feasibility of using an indirect method for making minimally invasive estimates of nanoparticle absorption that might be expanded to analyse a variety of geometries and particles of interest.

A Mechanistic Design Approach for Graphite Nanoplatelet (GNP) Reinforced Asphalt Mixtures for Low-Temperature Applications

DOT National Transportation Integrated Search

2018-01-01

This report explores the application of a discrete computational model for predicting the fracture behavior of asphalt mixtures at low temperatures based on the results of simple laboratory experiments. In this discrete element model, coarse aggregat...

Effects of Photochemically-Aged Atmospheres on Allergic Responses in Mice

EPA Science Inventory

Although air pollution is a complex mixture consisting of multiple gaseous and particulate components, current regulations and research approaches often focus on single pollutants. To better assess the impact of air pollution mixtures on respiratory health, we investigated the ef...

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

PubMed

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

2002-03-01

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

Sleep-promoting effects of a GABA/5-HTP mixture: Behavioral changes and neuromodulation in an invertebrate model.

PubMed

Hong, Ki-Bae; Park, Yooheon; Suh, Hyung Joo

2016-04-01

This study was to investigate the sleep promoting effects of combined γ-aminobutyric acid (GABA) and 5-hydroxytryptophan (5-HTP), by examining neuronal processes governing mRNA level alterations, as well as assessing neuromodulator concentrations, in a fruit fly model. Behavioral assays were applied to investigate subjective nighttime activity, sleep episodes, and total duration of subjective nighttime sleep of two amino acids and GABA/5-HTP mixture with caffeine treated flies. Also, real-time PCR and HPLC analysis were applied to analyze the signaling pathway. Subjective nighttime activity and sleep patterns of individual flies significantly decreased with 1% GABA treatment in conjunction with 0.1% 5-HTP treatment (p<0.001). Furthermore, GABA/5-HTP mixture resulted in significant differences between groups related to sleep patterns (40%, p<0.017) and significantly induced subjective nighttime sleep in the awake model (p<0.003). These results related to transcript levels of the GABAB receptor (GABAB-R1) and serotonin receptor (5-HT1A), compared to the control group. In addition, GABA/5-HTP mixture significantly increased GABA levels 1h and 12h following treatment (2.1 fold and 1.2 fold higher than the control, respectively) and also increased 5-HTP levels (0 h: 1.01 μg/protein, 12h: 3.45 μg/protein). In this regard, we successfully demonstrated that using a GABA/5-HTP mixture modulates subjective nighttime activity, sleep episodes, and total duration of subjective nighttime sleep to a greater extent than single administration of each amino acid, and that this modulation occurs via GABAergic and serotonergic signaling. Copyright © 2016 Elsevier Inc. All rights reserved.

Analytic Complexity and Challenges in Identifying Mixtures of Exposures Associated with Phenotypes in the Exposome Era.

PubMed

Patel, Chirag J

2017-01-01

Mixtures, or combinations and interactions between multiple environmental exposures, are hypothesized to be causally linked with disease and health-related phenotypes. Established and emerging molecular measurement technologies to assay the exposome , the comprehensive battery of exposures encountered from birth to death, promise a new way of identifying mixtures in disease in the epidemiological setting. In this opinion, we describe the analytic complexity and challenges in identifying mixtures associated with phenotype and disease. Existing and emerging machine-learning methods and data analytic approaches (e.g., "environment-wide association studies" [EWASs]), as well as large cohorts may enhance possibilities to identify mixtures of correlated exposures associated with phenotypes; however, the analytic complexity of identifying mixtures is immense. If the exposome concept is realized, new analytical methods and large sample sizes will be required to ascertain how mixtures are associated with disease. The author recommends documenting prevalent correlated exposures and replicated main effects prior to identifying mixtures.

Modeling the phase behavior of H2S+n-alkane binary mixtures using the SAFT-VR+D approach.

PubMed

dos Ramos, M Carolina; Goff, Kimberly D; Zhao, Honggang; McCabe, Clare

2008-08-07

A statistical associating fluid theory for potential of variable range has been recently developed to model dipolar fluids (SAFT-VR+D) [Zhao and McCabe, J. Chem. Phys. 2006, 125, 104504]. The SAFT-VR+D equation explicitly accounts for dipolar interactions and their effect on the thermodynamics and structure of a fluid by using the generalized mean spherical approximation (GMSA) to describe a reference fluid of dipolar square-well segments. In this work, we apply the SAFT-VR+D approach to real mixtures of dipolar fluids. In particular, we examine the high-pressure phase diagram of hydrogen sulfide+n-alkane binary mixtures. Hydrogen sulfide is modeled as an associating spherical molecule with four off-center sites to mimic hydrogen bonding and an embedded dipole moment (micro) to describe the polarity of H2S. The n-alkane molecules are modeled as spherical segments tangentially bonded together to form chains of length m, as in the original SAFT-VR approach. By using simple Lorentz-Berthelot combining rules, the theoretical predictions from the SAFT-VR+D equation are found to be in excellent overall agreement with experimental data. In particular, the theory is able to accurately describe the different types of phase behavior observed for these mixtures as the molecular weight of the alkane is varied: type III phase behavior, according to the scheme of classification by Scott and Konynenburg, for the H2S+methane system, type IIA (with the presence of azeotropy) for the H2S+ethane and+propane mixtures; and type I phase behavior for mixtures of H2S and longer n-alkanes up to n-decane. The theory is also able to predict in a qualitative manner the solubility of hydrogen sulfide in heavy n-alkanes.

New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water

NASA Astrophysics Data System (ADS)

Witek, Marcin L.; Garay, Michael J.; Diner, David J.; Bull, Michael A.; Seidel, Felix C.

2018-01-01

A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, best estimate AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥ 0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

New Approach to the Retrieval of AOD and its Uncertainty from MISR Observations Over Dark Water

NASA Astrophysics Data System (ADS)

Witek, M. L.; Garay, M. J.; Diner, D. J.; Bull, M. A.; Seidel, F.

2017-12-01

A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous Version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture, then used a combination of these values to compute the final, "best estimate" AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of a) the absolute values of the cost functions for each aerosol mixture, b) the widths of the cost function distributions as a function of AOD, and c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on arbitrary thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new Aerosol Retrieval Confidence Index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

Differential gene expression pattern in human mammary epithelial cells induced by realistic organochlorine mixtures described in healthy women and in women diagnosed with breast cancer.

PubMed

Rivero, Javier; Henríquez-Hernández, Luis Alberto; Luzardo, Octavio P; Pestano, José; Zumbado, Manuel; Boada, Luis D; Valerón, Pilar F

2016-03-30

Organochlorine pesticides (OCs) have been associated with breast cancer development and progression, but the mechanisms underlying this phenomenon are not well known. In this work, we evaluated the effects exerted on normal human mammary epithelial cells (HMEC) by the OC mixtures most frequently detected in healthy women (H-mixture) and in women diagnosed with breast cancer (BC-mixture), as identified in a previous case-control study developed in Spain. Cytotoxicity and gene expression profile of human kinases (n=68) and non-kinases (n=26) were tested at concentrations similar to those described in the serum of those cases and controls. Although both mixtures caused a down-regulation of genes involved in the ATP binding process, our results clearly indicate that both mixtures may exert a very different effect on the gene expression profile of HMEC. Thus, while BC-mixture up-regulated the expression of oncogenes associated to breast cancer (GFRA1 and BHLHB8), the H-mixture down-regulated the expression of tumor suppressor genes (EPHA4 and EPHB2). Our results indicate that the composition of the OC mixture could play a role in the initiation processes of breast cancer. In addition, the present results suggest that subtle changes in the composition and levels of pollutants involved in environmentally relevant mixtures might induce very different biological effects, which explain, at least partially, why some mixtures seem to be more carcinogenic than others. Nonetheless, our findings confirm that environmentally relevant pollutants may modulate the expression of genes closely related to carcinogenic processes in the breast, reinforcing the role exerted by environment in the regulation of genes involved in breast carcinogenesis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Enhancing the Benefit of the Chemical Mixture Methodology: A Report on Methodology Testing and Potential Approaches for Improving Performance

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

Yu, Xiao-Ying; Yao, Juan; He, Hua

2012-01-01

Extensive testing shows that the current version of the Chemical Mixture Methodology (CMM) is meeting its intended mission to provide conservative estimates of the health effects from exposure to airborne chemical mixtures. However, the current version of the CMM could benefit from several enhancements that are designed to improve its application of Health Code Numbers (HCNs) and employ weighting factors to reduce over conservatism.

New theoretical framework for designing nonionic surfactant mixtures that exhibit a desired adsorption kinetics behavior.

PubMed

Moorkanikkara, Srinivas Nageswaran; Blankschtein, Daniel

2010-12-21

How does one design a surfactant mixture using a set of available surfactants such that it exhibits a desired adsorption kinetics behavior? The traditional approach used to address this design problem involves conducting trial-and-error experiments with specific surfactant mixtures. This approach is typically time-consuming and resource-intensive and becomes increasingly challenging when the number of surfactants that can be mixed increases. In this article, we propose a new theoretical framework to identify a surfactant mixture that most closely meets a desired adsorption kinetics behavior. Specifically, the new theoretical framework involves (a) formulating the surfactant mixture design problem as an optimization problem using an adsorption kinetics model and (b) solving the optimization problem using a commercial optimization package. The proposed framework aims to identify the surfactant mixture that most closely satisfies the desired adsorption kinetics behavior subject to the predictive capabilities of the chosen adsorption kinetics model. Experiments can then be conducted at the identified surfactant mixture condition to validate the predictions. We demonstrate the reliability and effectiveness of the proposed theoretical framework through a realistic case study by identifying a nonionic surfactant mixture consisting of up to four alkyl poly(ethylene oxide) surfactants (C(10)E(4), C(12)E(5), C(12)E(6), and C(10)E(8)) such that it most closely exhibits a desired dynamic surface tension (DST) profile. Specifically, we use the Mulqueen-Stebe-Blankschtein (MSB) adsorption kinetics model (Mulqueen, M.; Stebe, K. J.; Blankschtein, D. Langmuir 2001, 17, 5196-5207) to formulate the optimization problem as well as the SNOPT commercial optimization solver to identify a surfactant mixture consisting of these four surfactants that most closely exhibits the desired DST profile. Finally, we compare the experimental DST profile measured at the surfactant mixture condition identified by the new theoretical framework with the desired DST profile and find good agreement between the two profiles.

Nonlinear hydrodynamic stability and transition; Proceedings of the IUTAM Symposium, Nice, France, Sept. 3-7, 1990

NASA Astrophysics Data System (ADS)

Theoretical and experimental research on nonlinear hydrodynamic stability and transition is presented. Bifurcations, amplitude equations, pattern in experiments, and shear flows are considered. Particular attention is given to bifurcations of plane viscous fluid flow and transition to turbulence, chaotic traveling wave covection, chaotic behavior of parametrically excited surface waves in square geometry, amplitude analysis of the Swift-Hohenberg equation, traveling wave convection in finite containers, focus instability in axisymmetric Rayleigh-Benard convection, scaling and pattern formation in flowing sand, dynamical behavior of instabilities in spherical gap flows, and nonlinear short-wavelength Taylor vortices. Also discussed are stability of a flow past a two-dimensional grid, inertia wave breakdown in a precessing fluid, flow-induced instabilities in directional solidification, structure and dynamical properties of convection in binary fluid mixtures, and instability competition for convecting superfluid mixtures.

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

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

Roberts, D.A.; Green, R.O.; Adams, J.B.

1997-12-01

Little research has focused on the use of imaging spectrometry for change detection. In this paper, the authors apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atmospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiative-transfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and shade. Temporal andmore » spatial patterns in endmember fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target.« less

High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines

PubMed Central

Yu, Channing; Mannan, Aristotle M.; Yvone, Griselda Metta; Ross, Kenneth N.; Zhang, Yan-Ling; Marton, Melissa A.; Taylor, Bradley R.; Crenshaw, Andrew; Gould, Joshua Z.; Tamayo, Pablo; Weir, Barbara A.; Tsherniak, Aviad; Wong, Bang; Garraway, Levi A.; Shamji, Alykhan F.; Palmer, Michelle A.; Foley, Michael A.; Winckler, Wendy; Schreiber, Stuart L.; Kung, Andrew L.; Golub, Todd R.

2016-01-01

Hundreds of genetically characterized cell lines are available for the discovery of genotype-specific cancer vulnerabilities. However, screening large numbers of compounds against large numbers of cell lines is currently impractical, and such experiments are often difficult to control1-4. Here, we report a method called PRISM that allows pooled screening of mixtures of cancer cell lines by labeling each cell line with 24-nucleotide barcodes. PRISM displayed the expected patterns of cell killing seen in conventional (unpooled) assays. In a screen of 102 cell lines across 8,400 compounds, PRISM led to the identification of BRD-7880 as a potent and highly specific inhibitor of aurora kinases B and C. Cell line pools also efficiently formed tumors as xenografts, and PRISM recapitulated the expected pattern of erlotinib sensitivity in vivo. PMID:26928769

Performance Evaluation and Durability Studies of Adhesive Bonds

NASA Astrophysics Data System (ADS)

Ranade, Shantanu Rajendra

In this thesis, four test approaches were developed to characterize the adhesion performance and durability of adhesive bonds for specific applications in areas spanning from structural adhesive joints to popular confectionaries such as chewing gum. In the first chapter, a double cantilever beam (DCB) specimen geometry is proposed for combinatorial fracture studies of structural adhesive bonds. This specimen geometry enabled the characterization of fracture energy vs. bondline thickness trends through fewer tests than those required during a conventional "one at a time" characterization approach, potentially offering a significant reduction in characterization times. The second chapter investigates the adhesive fracture resistance and crack path selection in adhesive joints containing patterns of discreet localized weak interfaces created using physical vapor deposition of copper. In a DCB specimen tested under mode-I conditions, fracture energy within the patterned regions scaled according to a simple rule of mixture, while reverse R-curve and R-curve type trends were observed in the regions surrounding weak interface patterns. Under mixed mode conditions such that bonding surface with patterns is subjected to axial tension, fracture energy did not show R-curve type trends while it was observed that a crack could be made to avoid exceptionally weak interfaces when loaded such that bonding surface with defects is subjected to axial compression. In the third chapter, an adaptation of the probe tack test is proposed to characterize the adhesion behavior of gum cuds. This test method allowed the introduction of substrates with well-defined surface energies and topologies to study their effects on gum cud adhesion. This approach and reported insights could potentially be useful in developing chewing gum formulations that facilitate easy removal of improperly discarded gum cuds from adhering surfaces. In the fourth chapter we highlight a procedure to obtain insights into the long-term performance of silicone sealants designed for load-bearing applications such as solar panel support sealants. Using small strain constitutive tests and time-temperature-superposition principle, thermal shift factors were obtained and successfully used to characterize the creep rupture master curves for specific joint configurations, leading to insights into delayed failures corresponding to three years through experiments carried out in one month.

Mixture models in diagnostic meta-analyses--clustering summary receiver operating characteristic curves accounted for heterogeneity and correlation.

PubMed

Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario

2015-01-01

Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.

Simple area determination of strongly overlapping ion mobility peaks.

PubMed

Borovcová, Lucie; Hermannová, Martina; Pauk, Volodymyr; Šimek, Matěj; Havlíček, Vladimír; Lemr, Karel

2017-08-15

Coupling of ion mobility with mass spectrometry has brought new frontiers in separation and quantitation of a wide range of isobaric/isomeric compounds. Ion mobility spectrometry may separate ions possessing the identical molecular formula but having different molecular shapes. The separation space in most commercially available instruments is limited and rarely the mobility resolving power exceeds one hundred. From this perspective, new approaches allowing for extracting individual compound signals out of a more complex mixture are needed. In this work we present a new simple analytical approach based on fitting of arrival time distribution (ATD) profiles by Gaussian functions and generating of ATD functions. These ATD functions well describe even distorted ion mobility peaks of individual compounds and allow for extracting their peaks from mobilograms of mixtures. Contrary to classical integration, our approach works well with irregular overlapping peaks. Using mobilograms of standards to generate ATD functions, poorly separated compounds, e.g. isomers, with identical mass spectra representing a hard to solve task for various chemometric methods can be easily distinguished by our procedure. Alternatively ATD functions can be obtained from ATD profiles of ions unique to individual mixture components (if such ions exist) and mobilograms of standards are not required. On a set of hyaluronan-derived oligosaccharides we demonstrated excellent ATD repeatability enabling the resolution of binary mixtures, including mixtures with minor component level about 5%. Ion mobility quantitative data of isomers were confirmed by high performance liquid chromatography. Copyright © 2017 Elsevier B.V. All rights reserved.

Probability density function characterization for aggregated large-scale wind power based on Weibull mixtures

DOE PAGES

Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; ...

2016-02-02

Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power datamore » are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.« less

[Physicochemical properties of suplatast tosilate racemate and enantiomers].

PubMed

Ushio, T; Endo, K; Yamamoto, K

1996-11-01

The physicochemical properties of the enantiomer and racemates of suplatast tosilate (ST) were investigated by means of infrared spectroscopy, solid-state 13C CP/MAS NMR spectroscopy, thermal analysis, and X-ray diffraction analysis, and by measuring the solubility and hygroscopy. The infrared and NMR spectra and X-ray diffraction pattern of the enantiomer were distinctly different from those of the racemate. The melting point of the enantiomer was lower than that of the racemate by 5 degrees C, while the solubility of the enantiomer was 1.3 times higher than that of the racemate. The hygroscopic rate of the enantiomer was greater than that of the racemate. These results suggested that ST was classified into a racemic compound crystal. Furthermore, by comparing the relative peak intensity ratios on X-ray diffraction patterns of the crystals with various optical purities prepared by recrystallization, it was found that a mixture of racemic compound crystals and either of racemic mixture crystals or racemic solid solutions was obtained by recrystallization of ST in the content of 0 to 64%ee, while the recrystallization of ST in the content of more than 64%ee led to the formation of racemic mixture crystals or racemic solid solutions.

Separation/extraction, detection, and interpretation of DNA mixtures in forensic science (review).

PubMed

Tao, Ruiyang; Wang, Shouyu; Zhang, Jiashuo; Zhang, Jingyi; Yang, Zihao; Sheng, Xiang; Hou, Yiping; Zhang, Suhua; Li, Chengtao

2018-05-25

Interpreting mixed DNA samples containing material from multiple contributors has long been considered a major challenge in forensic casework, especially when encountering low-template DNA (LT-DNA) or high-order mixtures that may involve missing alleles (dropout) and unrelated alleles (drop-in), among others. In the last decades, extraordinary progress has been made in the analysis of mixed DNA samples, which has led to increasing attention to this research field. The advent of new methods for the separation and extraction of DNA from mixtures, novel or jointly applied genetic markers for detection and reliable interpretation approaches for estimating the weight of evidence, as well as the powerful massively parallel sequencing (MPS) technology, has greatly extended the range of mixed samples that can be correctly analyzed. Here, we summarized the investigative approaches and progress in the field of forensic DNA mixture analysis, hoping to provide some assistance to forensic practitioners and to promote further development involving this issue.

Space-time variation of respiratory cancers in South Carolina: a flexible multivariate mixture modeling approach to risk estimation.

PubMed

Carroll, Rachel; Lawson, Andrew B; Kirby, Russell S; Faes, Christel; Aregay, Mehreteab; Watjou, Kevin

2017-01-01

Many types of cancer have an underlying spatiotemporal distribution. Spatiotemporal mixture modeling can offer a flexible approach to risk estimation via the inclusion of latent variables. In this article, we examine the application and benefits of using four different spatiotemporal mixture modeling methods in the modeling of cancer of the lung and bronchus as well as "other" respiratory cancer incidences in the state of South Carolina. Of the methods tested, no single method outperforms the other methods; which method is best depends on the cancer under consideration. The lung and bronchus cancer incidence outcome is best described by the univariate modeling formulation, whereas the "other" respiratory cancer incidence outcome is best described by the multivariate modeling formulation. Spatiotemporal multivariate mixture methods can aid in the modeling of cancers with small and sparse incidences when including information from a related, more common type of cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

An experimental approach aiming the production of a gas mixture composed of hydrogen and methane from biomass as natural gas substitute in industrial applications.

PubMed

Kraussler, Michael; Schindler, Philipp; Hofbauer, Hermann

2017-08-01

This work presents an experimental approach aiming the production of a gas mixture composed of H 2 and CH 4 , which should serve as natural gas substitute in industrial applications. Therefore, a lab-scale process chain employing a water gas shift unit, scrubbing units, and a pressure swing adsorption unit was operated with tar-rich product gas extracted from a commercial dual fluidized bed biomass steam gasification plant. A gas mixture with a volumetric fraction of about 80% H 2 and 19% CH 4 and with minor fractions of CO and CO 2 was produced by employing carbon molecular sieve as adsorbent. Moreover, the produced gas mixture had a lower heating value of about 15.5MJ·m -3 and a lower Wobbe index of about 43.4MJ·m -3 , which is similar to the typical Wobbe index of natural gas. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Cárdenas, Rosa Elia, E-mail: recarde1@uiwtx.edu; Stewart, Kenneth D.; Cowgill, Donald F., E-mail: dfcowgi@sandia.gov

In this study, the authors developed an approach for accurately quantifying the helium content in a gas mixture also containing hydrogen and methane using commercially available getters. The authors performed a systematic study to examine how both H{sub 2} and CH{sub 4} can be removed simultaneously from the mixture using two SAES St 172{sup ®} getters operating at different temperatures. The remaining He within the gas mixture can then be measured directly using a capacitance manometer. The optimum combination involved operating one getter at 650 °C to decompose the methane, and the second at 110 °C to remove the hydrogen. This approachmore » eliminated the need to reactivate the getters between measurements, thereby enabling multiple measurements to be made within a short time interval, with accuracy better than 1%. The authors anticipate that such an approach will be particularly useful for quantifying the He-3 in mixtures that include tritium, tritiated methane, and helium-3. The presence of tritiated methane, generated by tritium activity, often complicates such measurements.« less

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Chemometric Data Analysis for Deconvolution of Overlapped Ion Mobility Profiles

NASA Astrophysics Data System (ADS)

Zekavat, Behrooz; Solouki, Touradj

2012-11-01

We present the details of a data analysis approach for deconvolution of the ion mobility (IM) overlapped or unresolved species. This approach takes advantage of the ion fragmentation variations as a function of the IM arrival time. The data analysis involves the use of an in-house developed data preprocessing platform for the conversion of the original post-IM/collision-induced dissociation mass spectrometry (post-IM/CID MS) data to a Matlab compatible format for chemometric analysis. We show that principle component analysis (PCA) can be used to examine the post-IM/CID MS profiles for the presence of mobility-overlapped species. Subsequently, using an interactive self-modeling mixture analysis technique, we show how to calculate the total IM spectrum (TIMS) and CID mass spectrum for each component of the IM overlapped mixtures. Moreover, we show that PCA and IM deconvolution techniques provide complementary results to evaluate the validity of the calculated TIMS profiles. We use two binary mixtures with overlapping IM profiles, including (1) a mixture of two non-isobaric peptides (neurotensin (RRPYIL) and a hexapeptide (WHWLQL)), and (2) an isobaric sugar isomer mixture of raffinose and maltotriose, to demonstrate the applicability of the IM deconvolution.

Bayesian Hierarchical Grouping: perceptual grouping as mixture estimation

PubMed Central

Froyen, Vicky; Feldman, Jacob; Singh, Manish

2015-01-01

We propose a novel framework for perceptual grouping based on the idea of mixture models, called Bayesian Hierarchical Grouping (BHG). In BHG we assume that the configuration of image elements is generated by a mixture of distinct objects, each of which generates image elements according to some generative assumptions. Grouping, in this framework, means estimating the number and the parameters of the mixture components that generated the image, including estimating which image elements are “owned” by which objects. We present a tractable implementation of the framework, based on the hierarchical clustering approach of Heller and Ghahramani (2005). We illustrate it with examples drawn from a number of classical perceptual grouping problems, including dot clustering, contour integration, and part decomposition. Our approach yields an intuitive hierarchical representation of image elements, giving an explicit decomposition of the image into mixture components, along with estimates of the probability of various candidate decompositions. We show that BHG accounts well for a diverse range of empirical data drawn from the literature. Because BHG provides a principled quantification of the plausibility of grouping interpretations over a wide range of grouping problems, we argue that it provides an appealing unifying account of the elusive Gestalt notion of Prägnanz. PMID:26322548

Enhancement of selectivity and resolution in the enantioseparation of uncharged compounds using mixtures of oppositely charged cyclodextrins in capillary electrophoresis.

PubMed

Abushoffa, Adel M; Fillet, Marianne; Servais, Anne-Catherine; Hubert, Philippe; Crommen, Jacques

2003-01-01

The enantiomeric separation of some nonsteroidal anti-inflammatory drugs (NSAIDs) was investigated in capillary electrophoresis (CE) using dual systems with mixtures of charged cyclodextrin (CD) derivatives. A significant enhancement of selectivity and resolution could be achieved in the enantioseparation of these analytes in their uncharged form by the simultaneous addition of two oppositely charged CD derivatives to the background electrolyte. The combination of the single-isomer cationic CD, permethyl-6-monoamino-6-monodeoxy-beta-CD (PMMAbetaCD) and the single-isomer polyanionic CD, heptakis-6-sulfato-beta-cyclodextrin (HSbetaCD) in a pH 2.5 phosphoric acid-triethanolamine buffer, was designed and employed for the enantioseparation of profens. The improvement in selectivity and resolution can be attributed to the fact that the two CDs, which lead to independent and enantioselective complexation with the analyte enantiomers, have not only opposite effects on the electrophoretic mobility of these compounds but also opposite affinity patterns towards the enantiomers of these compounds. Binding constants for these enantiomers with each CD were determined using linear regression approach, in order to be able to predict the effect of the concentrations of the two CDs on enantiomeric selectivity and resolution in such dual systems.

Utilization of oriented crystal growth for screening of aromatic carboxylic acids cocrystallization with urea

NASA Astrophysics Data System (ADS)

Przybyłek, Maciej; Ziółkowska, Dorota; Kobierski, Mirosław; Mroczyńska, Karina; Cysewski, Piotr

2016-01-01

The possibility of molecular complex formation in the solid state of urea with benzoic acid analogues was measured directly on the crystallite films deposited on the glass surface using powder X-ray diffractometry (PXRD). Obtained solid mixtures were also analyzed using Fourier transform infrared spectroscopy (FTIR). The simple droplet evaporation method was found to be efficient, robust, fast and cost-preserving approach for first stage cocrystal screening. Additionally, the application of orientation effect to cocrystal screening simplifies the analysis due to damping of majority of diffraction signals coming from coformers. During validation phase the proposed approach successfully reproduced both positive cases of cocrystallization (urea:salicylic acid and urea:4-hydroxy benzoic acid) as well as pairs of co-formers immiscible in the solid state (urea:benzoic acid and urea:acetylsalicylic acids). Based on validated approach new cocrystals of urea were identified in complexes with 3-hydroxybenzoic acid, 2,4-dihydroxybenzoic acid, 2,5-dihydroxybenzoic acid, 2,6-dihydroxybenzoic acid and 3,5-dihydroxybenzoic acid. In all cases formation of multicomponent crystal phase was confirmed by the appearance of new reflexes on the diffraction patterns and FTIR absorption band shifts of O-H and N-H groups.

Discrim: a computer program using an interactive approach to dissect a mixture of normal or lognormal distributions

USGS Publications Warehouse

Bridges, N.J.; McCammon, R.B.

1980-01-01

DISCRIM is an interactive computer graphics program that dissects mixtures of normal or lognormal distributions. The program was written in an effort to obtain a more satisfactory solution to the dissection problem than that offered by a graphical or numerical approach alone. It combines graphic and analytic techniques using a Tektronix1 terminal in a time-share computing environment. The main program and subroutines were written in the FORTRAN language. ?? 1980.

Kirkwood–Buff integrals for ideal solutions

PubMed Central

Ploetz, Elizabeth A.; Bentenitis, Nikolaos; Smith, Paul E.

2010-01-01

The Kirkwood–Buff (KB) theory of solutions is a rigorous theory of solution mixtures which relates the molecular distributions between the solution components to the thermodynamic properties of the mixture. Ideal solutions represent a useful reference for understanding the properties of real solutions. Here, we derive expressions for the KB integrals, the central components of KB theory, in ideal solutions of any number of components corresponding to the three main concentration scales. The results are illustrated by use of molecular dynamics simulations for two binary solutions mixtures, benzene with toluene, and methanethiol with dimethylsulfide, which closely approach ideal behavior, and a binary mixture of benzene and methanol which is nonideal. Simulations of a quaternary mixture containing benzene, toluene, methanethiol, and dimethylsulfide suggest this system displays ideal behavior and that ideal behavior is not limited to mixtures containing a small number of components. PMID:20441282

Experimental and numerical investigation of laminar flame speeds of hydrogen/carbon monoxide/carbon dioxide/nitrogen mixtures

NASA Astrophysics Data System (ADS)

Natarajan, Jayaprakash

Coal derived synthetic gas (syngas) fuel is a promising solution for today's increasing demand for clean and reliable power. Syngas fuels are primarily mixtures of H2 and CO, often with large amounts of diluents such as N2, CO2, and H2O. The specific composition depends upon the fuel source and gasification technique. This requires gas turbine designers to develop fuel flexible combustors capable of operating with high conversion efficiency while maintaining low emissions for a wide range of syngas tact mixtures. Design tools often used in combustor development require data on various fundamental gas combustion properties. For example, laminar flame speed is often an input as it has a significant impact upon the size and static stability of the combustor. Moreover it serves as a good validation parameter for leading kinetic models used for detailed combustion simulations. Thus the primary objective of this thesis is measurement of laminar flame speeds of syngas fuel mixtures at conditions relevant to ground-power gas turbines. To accomplish this goal, two flame speed measurement approaches were developed: a Bunsen flame approach modified to use the reaction zone area in order to reduce the influence of flame curvature on the measured flame speed and a stagnation flame approach employing a rounded bluff body. The modified Bunsen flame approach was validated against stretch-corrected approaches over a range of fuels and test conditions; the agreement is very good (less than 10% difference). Using the two measurement approaches, extensive flame speed information were obtained for lean syngas mixtures at a range of conditions: (1) 5 to 100% H2 in the H2/CO fuel mixture; (2) 300-700 K preheat temperature; (3) 1 to 15 atm pressure, and (4) 0-70% dilution with CO2 or N2. The second objective of this thesis is to use the flame speed data to validate leading kinetic mechanisms for syngas combustion. Comparisons of the experimental flame speeds to those predicted using detailed numerical simulations of strained and untrained laminar flames indicate that all the current kinetic mechanisms tend to over predict the increase in flame speed with preheat temperature for medium and high H2 content fuel mixtures. A sensitivity analysis that includes reported uncertainties in rate constants reveals that the errors in the rate constants of the reactions involving HO 2 seem to be the most likely cause for the observed higher preheat temperature dependence of the flame speeds. To enhance the accuracy of the current models, a more detailed sensitivity analysis based on temperature dependent reaction rate parameters should be considered as the problem seems to be in the intermediate temperature range (˜800-1200 K).

Time-dependent patterns in quasivertical cylindrical binary convection.

PubMed

Alonso, Arantxa; Mercader, Isabel; Batiste, Oriol

2018-02-01

This paper reports on numerical investigations of the effect of a slight inclination α on pattern formation in a shallow vertical cylindrical cell heated from below for binary mixtures with a positive value of the Soret coefficient. By using direct numerical simulation of the three-dimensional Boussinesq equations with Soret effect in cylindrical geometry, we show that a slight inclination of the cell in the range α≈0.036rad=2^{∘} strongly influences pattern selection. The large-scale shear flow (LSSF) induced by the small tilt of gravity overcomes the squarelike arrangements observed in noninclined cylinders in the Soret regime, stratifies the fluid along the direction of inclination, and produces an enhanced separation of the two components of the mixture. The competition between shear effects and horizontal and vertical buoyancy alters significantly the dynamics observed in noninclined convection. Additional unexpected time-dependent patterns coexist with the basic LSSF. We focus on an unsual periodic state recently discovered in an experiment, the so-called superhighway convection state (SHC), in which ascending and descending regions of fluid move in opposite directions. We provide numerical confirmation that Boussinesq Navier-Stokes equations with standard boundary conditions contain the essential ingredients that allow for the existence of such a state. Also, we obtain a persistent heteroclinic structure where regular oscillations between a SHC pattern and a state of nearly stationary longitudinal rolls take place. We characterize numerically these time-dependent patterns and investigate the dynamics around the threshold of convection.

Time-dependent patterns in quasivertical cylindrical binary convection

NASA Astrophysics Data System (ADS)

Alonso, Arantxa; Mercader, Isabel; Batiste, Oriol

2018-02-01

This paper reports on numerical investigations of the effect of a slight inclination α on pattern formation in a shallow vertical cylindrical cell heated from below for binary mixtures with a positive value of the Soret coefficient. By using direct numerical simulation of the three-dimensional Boussinesq equations with Soret effect in cylindrical geometry, we show that a slight inclination of the cell in the range α ≈0.036 rad =2∘ strongly influences pattern selection. The large-scale shear flow (LSSF) induced by the small tilt of gravity overcomes the squarelike arrangements observed in noninclined cylinders in the Soret regime, stratifies the fluid along the direction of inclination, and produces an enhanced separation of the two components of the mixture. The competition between shear effects and horizontal and vertical buoyancy alters significantly the dynamics observed in noninclined convection. Additional unexpected time-dependent patterns coexist with the basic LSSF. We focus on an unsual periodic state recently discovered in an experiment, the so-called superhighway convection state (SHC), in which ascending and descending regions of fluid move in opposite directions. We provide numerical confirmation that Boussinesq Navier-Stokes equations with standard boundary conditions contain the essential ingredients that allow for the existence of such a state. Also, we obtain a persistent heteroclinic structure where regular oscillations between a SHC pattern and a state of nearly stationary longitudinal rolls take place. We characterize numerically these time-dependent patterns and investigate the dynamics around the threshold of convection.

Effects of glyphosate and two herbicide mixtures on microbial communities in prairie wetland ecosystems: a mesocosm approach.

PubMed

Sura, Srinivas; Waiser, Marley; Tumber, Vijay; Lawrence, John R; Cessna, Allan J; Glozier, Nancy

2012-01-01

A multitrophic outdoor mesocosm system was used to mimic a wetland ecosystem and to investigate the effects of glyphosate and two herbicide mixtures on wetland microbial communities. The glyphosate concentration used was 1000 times the environmentally relevant concentration (ERC). One herbicide mixture consisted of six auxin-type herbicides (2,4-D, MCPA, clopyralid, dicamba, dichlorprop, mecoprop), each at 1000 times the ERC. The second mixture was comprised of eight herbicides, including the six auxin-type herbicides as well as bromoxynil and glyphosate. For this mixture, a dose-response approach was used to treat mesocosms with the ERCs of each herbicide as the base concentration. Algal biomass and production and bacterial production and numbers for pelagic and attached communities were measured at different times over a 22-d period. The experimental results indicate that the eight-herbicide mixture, even at low concentrations, produced negative effects on microbial communities. Glyphosate on its own suppressed algal biomass and production for the duration of the study in pelagic and biofilm communities. Algal biomass and production, although initially depressed in the auxin-type herbicide treatment, were stimulated from Day 9 until experiment end. Due to their similar modes of action, the effects of this herbicide mixture appear to be a result of concentration addition. Such negative effects, however, were brief, and microbial communities recovered from herbicide exposure. Based on evidence presented in this study, it appears that glyphosate has a higher potential to inhibit primary production and chlorophyll content in pelagic and attached wetland algal communities than the auxin-type herbicide mixture. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures.

PubMed

Liu, Shelley H; Bobb, Jennifer F; Lee, Kyu Ha; Gennings, Chris; Claus Henn, Birgit; Bellinger, David; Austin, Christine; Schnaas, Lourdes; Tellez-Rojo, Martha M; Hu, Howard; Wright, Robert O; Arora, Manish; Coull, Brent A

2018-07-01

The impact of neurotoxic chemical mixtures on children's health is a critical public health concern. It is well known that during early life, toxic exposures may impact cognitive function during critical time intervals of increased vulnerability, known as windows of susceptibility. Knowledge on time windows of susceptibility can help inform treatment and prevention strategies, as chemical mixtures may affect a developmental process that is operating at a specific life phase. There are several statistical challenges in estimating the health effects of time-varying exposures to multi-pollutant mixtures, such as: multi-collinearity among the exposures both within time points and across time points, and complex exposure-response relationships. To address these concerns, we develop a flexible statistical method, called lagged kernel machine regression (LKMR). LKMR identifies critical exposure windows of chemical mixtures, and accounts for complex non-linear and non-additive effects of the mixture at any given exposure window. Specifically, LKMR estimates how the effects of a mixture of exposures change with the exposure time window using a Bayesian formulation of a grouped, fused lasso penalty within a kernel machine regression (KMR) framework. A simulation study demonstrates the performance of LKMR under realistic exposure-response scenarios, and demonstrates large gains over approaches that consider each time window separately, particularly when serial correlation among the time-varying exposures is high. Furthermore, LKMR demonstrates gains over another approach that inputs all time-specific chemical concentrations together into a single KMR. We apply LKMR to estimate associations between neurodevelopment and metal mixtures in Early Life Exposures in Mexico and Neurotoxicology, a prospective cohort study of child health in Mexico City.

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

PubMed Central

Lo, Kenneth

2011-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components. PMID:22125375

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

PubMed

Lo, Kenneth; Gottardo, Raphael

2012-01-01

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

NEUROBEHAVIORAL EVALUATIONS OF BINARY AND TERTIARY MIXTURES OF CHEMICALS: LESSIONS LEARNING.

EPA Science Inventory

The classical approach to the statistical analysis of binary chemical mixtures is to construct full dose-response curves for one compound in the presence of a range of doses of the second compound (isobolographic analyses). For interaction studies using more than two chemicals, ...

Assessment of wastewater treatment plant effluent on fish reproduction utilizing the adverse outcome pathway conceptual framework

EPA Science Inventory

Wastewater treatment plant (WWTP) effluents are a known contributor of chemical mixture inputs into the environment. Whole effluent testing guidelines were developed to screen these complex mixtures for acute toxicity. However, efficient and cost-effective approaches for screenin...

PROCEDURES FOR DERIVING EQUILIBRIUM PARTITIONING BENCHMARKS (ESBS) FOR THE PROTECTION OF BENTHIC ORGANISM: PAH MIXTURES

EPA Science Inventory

This equilibrium partitioning sediment benchmark (ESB) document describes procedures to derive concentrations of PAH mixtures in sediment which are protective of the presence of benthic organisms. The equilibrium partitioning (EqP) approach was chosen because it accounts for t...

Exposure of Mammalian Cells to Air-Pollutant Mixtures at the Air-Liquid Interface

EPA Science Inventory

It has been widely accepted that exposure of mammalian cells to air-pollutant mixtures at the air-liquid interface is a more realistic approach than exposing cell under submerged conditions. The VITROCELL systems, are commercially available systems for air-liquid interface expo...

Birthdays and the Binary System: A Magical Mixture.

ERIC Educational Resources Information Center

Karp, Karen S.; Ronau, Robert N.

1997-01-01

Presents an activity involving the use of students' birth dates. Activity includes a classic binary representation of numerical values. In the Green Machine, Sorting Cards, and Window Cards, students observe, describe, and analyze patterns. (PVD)

Rapid method for determination of antimicrobial susceptibilities pattern of urinary bacteria

NASA Technical Reports Server (NTRS)

Picciolo, G. L.; Chapelle, E. W.; Barza, M. J.; Weinstein, L.; Tuttle, S. A.; Vellend, H.

1975-01-01

Method determines bacterial sensitivity to antimicrobial agents by measuring level of adenosine triphosphate remaining in the bacteria. Light emitted during reaction of sample with a mixture of luciferase and luciferin is measured.

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

Motevaselian, M. H.; Mashayak, S. Y.; Aluru, N. R., E-mail: aluru@illinois.edu

Empirical potential-based quasi-continuum theory (EQT) provides a route to incorporate atomistic detail into continuum framework such as the Nernst-Planck equation. EQT can also be used to construct a grand potential functional for classical density functional theory (cDFT). The combination of EQT and cDFT provides a simple and fast approach to predict the inhomogeneous density, potential profiles, and thermodynamic properties of confined fluids. We extend the EQT-cDFT approach to confined fluid mixtures and demonstrate it by simulating a mixture of methane and hydrogen inside slit-like channels of graphene. We show that the EQT-cDFT predictions for the structure of the confined fluidmore » mixture compare well with the molecular dynamics simulation results. In addition, our results show that graphene slit nanopores exhibit a selective adsorption of methane over hydrogen.« less

Gaussian mixture model based identification of arterial wall movement for computation of distension waveform.

PubMed

Patil, Ravindra B; Krishnamoorthy, P; Sethuraman, Shriram

2015-01-01

This work proposes a novel Gaussian Mixture Model (GMM) based approach for accurate tracking of the arterial wall and subsequent computation of the distension waveform using Radio Frequency (RF) ultrasound signal. The approach was evaluated on ultrasound RF data acquired using a prototype ultrasound system from an artery mimicking flow phantom. The effectiveness of the proposed algorithm is demonstrated by comparing with existing wall tracking algorithms. The experimental results show that the proposed method provides 20% reduction in the error margin compared to the existing approaches in tracking the arterial wall movement. This approach coupled with ultrasound system can be used to estimate the arterial compliance parameters required for screening of cardiovascular related disorders.

Landscape attributes and life history variability shape genetic structure of trout populations in a stream network

USGS Publications Warehouse

Neville, H.M.; Dunham, J.B.; Peacock, M.M.

2006-01-01

Spatial and temporal landscape patterns have long been recognized to influence biological processes, but these processes often operate at scales that are difficult to study by conventional means. Inferences from genetic markers can overcome some of these limitations. We used a landscape genetics approach to test hypotheses concerning landscape processes influencing the demography of Lahontan cutthroat trout in a complex stream network in the Great Basin desert of the western US. Predictions were tested with population- and individual-based analyses of microsatellite DNA variation, reflecting patterns of dispersal, population stability, and local effective population sizes. Complementary genetic inferences suggested samples from migratory corridors housed a mixture of fish from tributaries, as predicted based on assumed migratory life histories in those habitats. Also as predicted, populations presumed to have greater proportions of migratory fish or from physically connected, large, or high quality habitats had higher genetic variability and reduced genetic differentiation from other populations. Populations thought to contain largely non-migratory individuals generally showed the opposite pattern, suggesting behavioral isolation. Estimated effective sizes were small, and we identified significant and severe genetic bottlenecks in several populations that were isolated, recently founded, or that inhabit streams that desiccate frequently. Overall, this work suggested that Lahontan cutthroat trout populations in stream networks are affected by a combination of landscape and metapopulation processes. Results also demonstrated that genetic patterns can reveal unexpected processes, even within a system that is well studied from a conventional ecological perspective. ?? Springer 2006.

Photodynamic mechanisms induced by a combination of hypericin and a chlorin based-photosensitizer in head and neck squamous cell carcinoma cells.

PubMed

Gyenge, Emina Besic; Lüscher, Daniel; Forny, Patrick; Antoniol, Martina; Geisberger, Georg; Walt, Heinrich; Patzke, Greta; Maake, Caroline

2013-01-01

The aim of this study was to elucidate photodynamic therapy (PDT) effects mediated by hypericin and a liposomal meso-tetrahydroxyphenyl chlorin (mTHPC) derivative, with focus on their 1:1 mixture, on head and neck squamous cell carcinoma cell lines. Absorption, excitation and photobleaching were monitored using fluorescence spectrometry, showing the same spectral patterns for the mixture as measured for single photosensitizers. In the mixture mTHPC showed a prolonged photo-stability. Singlet oxygen yield for light-activated mTHPC was Φ(Δ) = 0.66, for hypericin Φ(Δ) = 0.25 and for the mixture Φ(Δ) = ~0.4. A linear increase of singlet oxygen yield for mTHPC and the mixture was found, whereas hypericin achieved saturation after 35 min. Reactive oxygen species fluorescence was only visible after hypericin and mixture-induced PDT. Cell viability was also more affected with these two treatment options under the selected conditions. Examination of death pathways showed that hypericin-mediated cell death was apoptotic, with mTHPC necrotic and the 1:1 mixture showed features of both. Changes in gene expression after PDT indicated strong up-regulation of selected heat-shock proteins. The application of photosensitizer mixtures with the features of reduced dark toxicity and combined apoptotic and necrotic cell death may be beneficial in clinical PDT. This will be the focus of our future investigations. © 2012 Wiley Periodicals, Inc. Photochemistry and Photobiology © 2012 The American Society of Photobiology.

An approach for evaluating the respiratory irritation of mixtures: application to metalworking fluids.

PubMed

Schaper, M M; Detwiler-Okabayashi, K A

1995-01-01

Recently, the sensory and pulmonary irritating properties of ten metalworking fluids (MWF) were assessed using a mouse bioassay. Relative potency of the MWFs was estimated, but it was not possible to identify the component(s) responsible for the the respiratory irritation induced by each MWF. One of the ten fluids, MWF "ET", produced sensory and pulmonary irritation in mice, and it was of moderate potency in comparison to the other nine MWFs. MWF "E" had three major components: tall oil fatty acids (TOFA), sodium sulfonate (SA), and paraffinic oil (PO). In the present study, the sensory and pulmonary irritating properties of these individual components of MWF "E" were evaluated. Mixtures of the three components were also prepared and similarly evaluated. This analysis revealed that the sensory irritation from MWF "E" was largely due to TOFA, whereas SA produced the pulmonary irritation observed with MWF "E". Both TOFA and SA were more potent irritants than was MWF "E", and the potency of TOFA and/or SA was diminished through combination with PO. There was no evidence of synergism of the components when combined to form MWF "E". This approach for identifying the biologically "active" component(s) in a mixture should be useful for other MWFs. Furthermore, the approach should be easily adapted for other applications involving concerns with mixtures.

Determination of 54 pesticides in waters of the Iberian Douro River estuary and risk assessment of environmentally relevant mixtures using theoretical approaches and Artemia salina and Daphnia magna bioassays.

PubMed

Cruzeiro, Catarina; Amaral, Sofia; Rocha, Eduardo; Rocha, Maria João

2017-11-01

As a case study, the estuary of the international Douro River (Iberian Peninsula) was sampled over a year (2010) at six sampling sites to determine the presence of 56 pesticides of different categories (insecticides, herbicides, and fungicides). 96% of measured pesticides were detected in 79% of the quantified samples. Individual average pesticide concentrations ranged from 39 to 1 265ng/L, indicating a ubiquitous presence of the selected compounds; moreover, twelve pesticides were above the 2013/39/EU Directive limits. Due to its highly impacted profile, a theoretical hazard assessment was done considering the average and maximum environmental mixtures of all measured pesticides to identify the most sensitive trophic level. For both environmental mixtures, the theoretical approach suggested that invertebrates were the most sensitive group. Therefore, short-time exposure assays using both invertebrates Artemia salina and Daphnia magna, were done using the referred mixtures. Data demonstrated significant toxic effects ─ high mortality rate and abnormal swimming behaviour ─ of the exposed animals. Both approaches (theoretical and experimental) support the analytical results, alerting for an intervention on this estuarine environment and of other comparable. Copyright © 2017 Elsevier Inc. All rights reserved.

Ground-Based Aerosol Measurements | Science Inventory ...

EPA Pesticide Factsheets

Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomon et al. 2014) as well as in research studies. In this approach, air, at a specified flow rate and time period, is typically drawn through an inlet, usually a size selective inlet, and then drawn through filters, 1 INTRODUCTION Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomo

Method optimization for drug impurity profiling in supercritical fluid chromatography: Application to a pharmaceutical mixture.

PubMed

Muscat Galea, Charlene; Didion, David; Clicq, David; Mangelings, Debby; Vander Heyden, Yvan

2017-12-01

A supercritical chromatographic method for the separation of a drug and its impurities has been developed and optimized applying an experimental design approach and chromatogram simulations. Stationary phase screening was followed by optimization of the modifier and injection solvent composition. A design-of-experiment (DoE) approach was then used to optimize column temperature, back-pressure and the gradient slope simultaneously. Regression models for the retention times and peak widths of all mixture components were built. The factor levels for different grid points were then used to predict the retention times and peak widths of the mixture components using the regression models and the best separation for the worst separated peak pair in the experimental domain was identified. A plot of the minimal resolutions was used to help identifying the factor levels leading to the highest resolution between consecutive peaks. The effects of the DoE factors were visualized in a way that is familiar to the analytical chemist, i.e. by simulating the resulting chromatogram. The mixture of an active ingredient and seven impurities was separated in less than eight minutes. The approach discussed in this paper demonstrates how SFC methods can be developed and optimized efficiently using simple concepts and tools. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of skin oil by FT-IR spectroscopy

NASA Astrophysics Data System (ADS)

Dasarathy, Keshava B.; Chittur, Krishnan K.; Dasarathy, Belur V.

1996-11-01

Secreted skin oil is a complex mixture of lipids, cholesterol, fatty acids, and a large number of other components. Its composition varies among individuals and with changes in physiology. In this paper, the feasibility of obtaining reproducible spectra of skin oils from individuals with a very simple, noninvasive technique is reported. Using pattern recognition algorithms, spectra could be classified on the basis of ethnicity and gender. Differences in spectra between individuals were larger than those between replicate samples taken from the same individual. While there are easier techniques for gender and ethnic identification, our purpose in this paper is to show that information of some value exists in skin-oil spectra. We believe that this approach could be used for such practical discrimination problems such as the determination of high and low cholesterol levels if confirmatory information for training such classifiers were available.

Addressing potential prior-data conflict when using informative priors in proof-of-concept studies.

PubMed

Mutsvari, Timothy; Tytgat, Dominique; Walley, Rosalind

2016-01-01

Bayesian methods are increasingly used in proof-of-concept studies. An important benefit of these methods is the potential to use informative priors, thereby reducing sample size. This is particularly relevant for treatment arms where there is a substantial amount of historical information such as placebo and active comparators. One issue with using an informative prior is the possibility of a mismatch between the informative prior and the observed data, referred to as prior-data conflict. We focus on two methods for dealing with this: a testing approach and a mixture prior approach. The testing approach assesses prior-data conflict by comparing the observed data to the prior predictive distribution and resorting to a non-informative prior if prior-data conflict is declared. The mixture prior approach uses a prior with a precise and diffuse component. We assess these approaches for the normal case via simulation and show they have some attractive features as compared with the standard one-component informative prior. For example, when the discrepancy between the prior and the data is sufficiently marked, and intuitively, one feels less certain about the results, both the testing and mixture approaches typically yield wider posterior-credible intervals than when there is no discrepancy. In contrast, when there is no discrepancy, the results of these approaches are typically similar to the standard approach. Whilst for any specific study, the operating characteristics of any selected approach should be assessed and agreed at the design stage; we believe these two approaches are each worthy of consideration. Copyright © 2015 John Wiley & Sons, Ltd.

Conceptual Model for Assessing Criteria Air Pollutants in a Multipollutant Context: A Modified Adverse Outcome Pathway Approach

EPA Science Inventory

Background: Air pollution consists of a complex mixture of particulate and gaseous components. Individual criteria and other hazardous air pollutants have been linked to adverse respiratory and cardiovascular health outcomes. However, assessing risk of air pollutant mixtures is d...

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...

MEASUREMENT AND PREDICTION OF THE RESISTIVITY OF ASH/SORBENT MIXTURES PRODUCED BY SULFUR OXIDE CONTROL PROCESSES

EPA Science Inventory

The report describes the development of (1) a modified procedure for obtaining consistent and reproducible laboratory resistivity values for mixtures of coal fly ash and partially spent sorbent, and (2) an approach for predicting resistivity based on the chemical composition of t...

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…

Development of a Relative Potency Factor (Rpf) Approach for Polycyclic Aromatic Hydrocarbon (PAH) Mixtures (External Review Draft)

EPA Science Inventory

EPA is conducting a peer review and public comment of the scientific basis supporting the human health hazard and dose-response assessment of polycyclic aromatic hydrocarbon (PAH) mixtures that when finalized will appear on the Integrated Risk Information System (IRIS) database. ...

Reactions of green lizards (Lacerta viridis) to major repellent compounds secreted by Graphosoma lineatum (Heteroptera: Pentatomidae).

PubMed

Gregorovičová, Martina; Černíková, Alena

2015-06-01

The chemical defence of Heteroptera is primarily based on repellent secretions which signal the potential toxicity of the bug to its predators. We tested the aversive reactions of green lizards (Lacerta viridis) towards the major compounds of the defensive secretion of Graphosoma lineatum, specifically: (i) a mixture of three aldehydes: (E)-hex-2-enal, (E)-oct-2-enal, (E)-dec-2-enal; (ii) a mixture of these three aldehydes and tridecane; (iii) oxoaldehyde: (E)-4-oxohex-2-enal; (iv) secretion extracted from metathoracic scent glands of G. lineatum adults and (v) hexane as a non-polar solvent. All chemicals were presented on a palatable food (Tenebrio molitor larvae). The aversive reactions of the green lizards towards the mealworms were evaluated by observing the approach latencies, attack latencies and approach-attack intervals. The green lizards exhibited a strong aversive reaction to the mixture of three aldehydes. Tridecane reduced the aversive reaction to the aldehyde mixture. Oxoaldehyde caused the weakest, but still significant, aversive reaction. The secretion from whole metathoracic scent glands also clearly had an aversive effect on the green lizards. Moreover, when a living specimen of G. lineatum or Pyrrhocoris apterus (another aposematic red-and-black prey) was presented to the green lizards before the trials with the aldehyde mixture, the aversive effect of the mixture was enhanced. In conclusion, the mixture of three aldehydes had the strong aversive effect and could signal the potential toxicity of G. lineatum to the green lizards. Copyright © 2015 Elsevier GmbH. All rights reserved.

Separation Potential for Multicomponent Mixtures: State-of-the Art of the Problem

NASA Astrophysics Data System (ADS)

Sulaberidze, G. A.; Borisevich, V. D.; Smirnov, A. Yu.

2017-03-01

Various approaches used in introducing a separation potential (value function) for multicomponent mixtures have been analyzed. It has been shown that all known potentials do not satisfy the Dirac-Peierls axioms for a binary mixture of uranium isotopes, which makes their practical application difficult. This is mainly due to the impossibility of constructing a "standard" cascade, whose role in the case of separation of binary mixtures is played by the ideal cascade. As a result, the only universal search method for optimal parameters of the separation cascade is their numerical optimization by the criterion of the minimum number of separation elements in it.

Transport properties of nonelectrolyte mixtures. IX. Viscosity coefficients for acetonitrile and for three mixtures of toluene+acetonitrile from 25 to 100°c at pressures up to 500 MPa

NASA Astrophysics Data System (ADS)

Dymond, J. H.; Awan, M. A.; Glen, N. F.; Isdale, J. D.

1991-05-01

A two-coil self-centering falling-body viscometer has been used to measure viscosity coefficients for acetonitrile and three binary mixtures of toluene+ acetonitrile at 25, 50, 75, and 100°C and pressures up to 500 MPa. The results for acetonitrile can be interpreted by an approach based on hard-sphere theory, with a roughness factor of 1.46. The binary-mixture data are well represented by the Grunberg and Nissan equation with a mixing parameter which is pressure and temperature dependent but composition independent.

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.

New approach in direct-simulation of gas mixtures

NASA Technical Reports Server (NTRS)

Chung, Chan-Hong; De Witt, Kenneth J.; Jeng, Duen-Ren

1991-01-01

Results are reported for an investigation of a new direct-simulation Monte Carlo method by which energy transfer and chemical reactions are calculated. The new method, which reduces to the variable cross-section hard sphere model as a special case, allows different viscosity-temperature exponents for each species in a gas mixture when combined with a modified Larsen-Borgnakke phenomenological model. This removes the most serious limitation of the usefulness of the model for engineering simulations. The necessary kinetic theory for the application of the new method to mixtures of monatomic or polyatomic gases is presented, including gas mixtures involving chemical reactions. Calculations are made for the relaxation of a diatomic gas mixture, a plane shock wave in a gas mixture, and a chemically reacting gas flow along the stagnation streamline in front of a hypersonic vehicle. Calculated results show that the introduction of different molecular interactions for each species in a gas mixture produces significant differences in comparison with a common molecular interaction for all species in the mixture. This effect should not be neglected for accurate DSMC simulations in an engineering context.

Mixture and odorant processing in the olfactory systems of insects: a comparative perspective.

PubMed

Clifford, Marie R; Riffell, Jeffrey A

2013-11-01

Natural olfactory stimuli are often complex mixtures of volatiles, of which the identities and ratios of constituents are important for odor-mediated behaviors. Despite this importance, the mechanism by which the olfactory system processes this complex information remains an area of active study. In this review, we describe recent progress in how odorants and mixtures are processed in the brain of insects. We use a comparative approach toward contrasting olfactory coding and the behavioral efficacy of mixtures in different insect species, and organize these topics around four sections: (1) Examples of the behavioral efficacy of odor mixtures and the olfactory environment; (2) mixture processing in the periphery; (3) mixture coding in the antennal lobe; and (4) evolutionary implications and adaptations for olfactory processing. We also include pertinent background information about the processing of individual odorants and comparative differences in wiring and anatomy, as these topics have been richly investigated and inform the processing of mixtures in the insect olfactory system. Finally, we describe exciting studies that have begun to elucidate the role of the processing of complex olfactory information in evolution and speciation.

Ultrasonic sensing for noninvasive characterization of oil-water-gas flow in a pipe

NASA Astrophysics Data System (ADS)

Chillara, Vamshi Krishna; Sturtevant, Blake T.; Pantea, Cristian; Sinha, Dipen N.

2017-02-01

A technique for noninvasive ultrasonic characterization of multiphase crude oil-water-gas flow is discussed. The proposed method relies on determining the sound speed in the mixture. First, important issues associated with making real-time noninvasive measurements are discussed. Then, signal processing approach adopted to determine the sound speed in the multiphase mixture is presented. Finally, results from controlled experiments on crude oil-water mixture in both the presence and absence of gas are presented.

Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Zhang, Yongping; Cao, Zhong

2018-03-01

The traffic safety research has developed spatiotemporal models to explore the variations in the spatial pattern of crash risk over time. Many studies observed notable benefits associated with the inclusion of spatial and temporal correlation and their interactions. However, the safety literature lacks sufficient research for the comparison of different temporal treatments and their interaction with spatial component. This study developed four spatiotemporal models with varying complexity due to the different temporal treatments such as (I) linear time trend; (II) quadratic time trend; (III) Autoregressive-1 (AR-1); and (IV) time adjacency. Moreover, the study introduced a flexible two-component mixture for the space-time interaction which allows greater flexibility compared to the traditional linear space-time interaction. The mixture component allows the accommodation of global space-time interaction as well as the departures from the overall spatial and temporal risk patterns. This study performed a comprehensive assessment of mixture models based on the diverse criteria pertaining to goodness-of-fit, cross-validation and evaluation based on in-sample data for predictive accuracy of crash estimates. The assessment of model performance in terms of goodness-of-fit clearly established the superiority of the time-adjacency specification which was evidently more complex due to the addition of information borrowed from neighboring years, but this addition of parameters allowed significant advantage at posterior deviance which subsequently benefited overall fit to crash data. The Base models were also developed to study the comparison between the proposed mixture and traditional space-time components for each temporal model. The mixture models consistently outperformed the corresponding Base models due to the advantages of much lower deviance. For cross-validation comparison of predictive accuracy, linear time trend model was adjudged the best as it recorded the highest value of log pseudo marginal likelihood (LPML). Four other evaluation criteria were considered for typical validation using the same data for model development. Under each criterion, observed crash counts were compared with three types of data containing Bayesian estimated, normal predicted, and model replicated ones. The linear model again performed the best in most scenarios except one case of using model replicated data and two cases involving prediction without including random effects. These phenomena indicated the mediocre performance of linear trend when random effects were excluded for evaluation. This might be due to the flexible mixture space-time interaction which can efficiently absorb the residual variability escaping from the predictable part of the model. The comparison of Base and mixture models in terms of prediction accuracy further bolstered the superiority of the mixture models as the mixture ones generated more precise estimated crash counts across all four models, suggesting that the advantages associated with mixture component at model fit were transferable to prediction accuracy. Finally, the residual analysis demonstrated the consistently superior performance of random effect models which validates the importance of incorporating the correlation structures to account for unobserved heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

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).

The effect of water on thermal stresses in polymer composites

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.

1994-01-01

The fundamentals of the thermodynamic theory of mixtures and continuum thermochemistry are reviewed for a mixture of condensed water and polymer. A specific mixture which is mechanically elastic with temperature and water concentration gradients present is considered. An expression for the partial pressure of water in the mixture is obtained based on certain assumptions regarding the thermodynamic state of the water in the mixture. Along with a simple diffusion equation, this partial pressure expression may be used to simulate the thermostructural behavior of polymer composite materials due to water in the free volumes of the polymer. These equations are applied to a specific polymer composite material during isothermal heating conditions. The thermal stresses obtained by the application of the theory are compared to measured results to verify the accuracy of the approach.

Spontaneous bacteriocin resistance in Listeria monocytogenes as a susceptibility screen for identifying different mechanisms of resistance and modes of action by bacteriocins of lactic acid bacteria.

PubMed

Macwana, Sunita; Muriana, Peter M

2012-01-01

A practical system was devised for grouping bacteriocins of lactic acid bacteria (LAB) based on mode of action as determined by changes in inhibitory activity to spontaneously-acquired bacteriocin resistance (Bac(R)). Wild type Listeria monocytogenes 39-2 was sensitive to five bacteriocins produced by 3 genera of LAB: pediocin PA-1 and pediocin Bac3 (Pediococcus), lacticin FS97 and lacticin FS56 (Lactococcus), and curvaticin FS47 (Lactobacillus). A spontaneous Bac(R) derivative of L. monocytogenes 39-2 obtained by selective recovery against lacticin FS56 provided complete resistance to the bacteriocin made by Lactococcus lactis FS56. The lacticin FS56-resistant strain of L. monocyotgenes 39-2 was also cross-resistant to curvaticin FS47 and pediocin PA-1, but not to lacticin FS97 or pediocin Bac3. The same pattern of cross-resistance was also observed with Bac(R) isolates obtained with L. monocytogenes Scott A-2. A spontaneous mutation that renders a strain cross-resistant to different bacteriocins indicates that they share a common mechanism of resistance due to similar modes of action of the bacteriocins. Spontaneous resistance was acquired to other bacteriocins (in aggregate) by following the same procedure against which the Bac(R) strain was still sensitive. In subsequent challenge assays, mixtures of bacteriocins of different modes of action provided greater inhibition than mixtures of bacteriocins of the same mode of action (as determined by our screening method). This study identifies a methodical approach to classify bacteriocins into functional groups based on mechanism of resistance (i.e., mode of action) that could be used for identifying the best mixture of bacteriocins for use as biopreservatives. Copyright © 2011 Elsevier B.V. All rights reserved.

Dispersal and population state of an endangered island lizard following a conservation translocation.

PubMed

Angeli, Nicole F; Lundgren, Ian F; Pollock, Clayton G; Hillis-Starr, Zandy M; Fitzgerald, Lee A

2018-03-01

Population size is widely used as a unit of ecological analysis, yet to estimate population size requires accounting for observed and latent heterogeneity influencing dispersion of individuals across landscapes. In newly established populations, such as when animals are translocated for conservation, dispersal and availability of resources influence patterns of abundance. We developed a process to estimate population size using N-mixture models and spatial models for newly established and dispersing populations. We used our approach to estimate the population size of critically endangered St. Croix ground lizards (Ameiva polops) five years after translocation of 57 individuals to Buck Island, an offshore island of St. Croix, United States Virgin Islands. Estimates of population size incorporated abiotic variables, dispersal limits, and operative environmental temperature available to the lizards to account for low species detection. Operative environmental temperature and distance from the translocation site were always important in fitting the N-mixture model indicating effects of dispersal and species biology on estimates of population size. We found that the population is increasing its range across the island by 5-10% every six months. We spatially interpolated site-specific abundance from the N-mixture model to the entire island, and we estimated 1,473 (95% CI, 940-1,802) St. Croix ground lizards on Buck Island in 2013 corresponding to survey results. This represents a 26-fold increase since the translocation. We predicted the future dispersal of the lizards to all habitats on Buck Island, with the potential for the population to increase by another five times in the future. Incorporating biologically relevant covariates as explicit parameters in population models can improve predictions of population size and the future spread of species introduced to new localities. © 2018 by the Ecological Society of America.

A Quantitative Determination of Magnetic Nanoparticle Separation Using On-Off Field Operation of Quadrupole Magnetic Field-Flow Fractionation (QMgFFF)

PubMed Central

Orita, Toru; Moore, Lee R.; Joshi, Powrnima; Tomita, Masahiro; Horiuchi, Takashi; Zborowski, Maciej

2014-01-01

Quadrupole Magnetic Field-Flow Fractionation (QMgFFF) is a technique for characterization of sub-micrometer magnetic particles based on their retention in the magnetic field from flowing suspensions. Different magnetic field strengths and volumetric flow rates were tested using on-off field application and two commercial nanoparticle preparations that significantly differed in their retention parameter, λ (by nearly 8-fold). The fractograms showed a regular pattern of higher retention (98.6% v. 53.3%) for the larger particle (200 nm v. 90 nm) at the higher flow rate (0.05 mL/min v. 0.01 mL/min) at the highest magnetic field (0.52 T), as expected because of its lower retention parameter. The significance of this approach is a demonstration of a system that is simpler in operation than a programmed field QMgFFF in applications to particle mixtures consisting of two distinct particle fractions. This approach could be useful for detection of unwanted particulate contaminants, especially important in industrial and biomedical applications. PMID:23842422

Fluorescence-based assay as a new screening tool for toxic chemicals

PubMed Central

Moczko, Ewa; Mirkes, Evgeny M.; Cáceres, César; Gorban, Alexander N.; Piletsky, Sergey

2016-01-01

Our study involves development of fluorescent cell-based diagnostic assay as a new approach in high-throughput screening method. This highly sensitive optical assay operates similarly to e-noses and e-tongues which combine semi-specific sensors and multivariate data analysis for monitoring biochemical processes. The optical assay consists of a mixture of environmental-sensitive fluorescent dyes and human skin cells that generate fluorescence spectra patterns distinctive for particular physico-chemical and physiological conditions. Using chemometric techniques the optical signal is processed providing qualitative information about analytical characteristics of the samples. This integrated approach has been successfully applied (with sensitivity of 93% and specificity of 97%) in assessing whether particular chemical agents are irritating or not for human skin. It has several advantages compared with traditional biochemical or biological assays and can impact the new way of high-throughput screening and understanding cell activity. It also can provide reliable and reproducible method for assessing a risk of exposing people to different harmful substances, identification active compounds in toxicity screening and safety assessment of drugs, cosmetic or their specific ingredients. PMID:27653274

Fluorescence-based assay as a new screening tool for toxic chemicals.

PubMed

Moczko, Ewa; Mirkes, Evgeny M; Cáceres, César; Gorban, Alexander N; Piletsky, Sergey

2016-09-22

Our study involves development of fluorescent cell-based diagnostic assay as a new approach in high-throughput screening method. This highly sensitive optical assay operates similarly to e-noses and e-tongues which combine semi-specific sensors and multivariate data analysis for monitoring biochemical processes. The optical assay consists of a mixture of environmental-sensitive fluorescent dyes and human skin cells that generate fluorescence spectra patterns distinctive for particular physico-chemical and physiological conditions. Using chemometric techniques the optical signal is processed providing qualitative information about analytical characteristics of the samples. This integrated approach has been successfully applied (with sensitivity of 93% and specificity of 97%) in assessing whether particular chemical agents are irritating or not for human skin. It has several advantages compared with traditional biochemical or biological assays and can impact the new way of high-throughput screening and understanding cell activity. It also can provide reliable and reproducible method for assessing a risk of exposing people to different harmful substances, identification active compounds in toxicity screening and safety assessment of drugs, cosmetic or their specific ingredients.

Fluorescence-based assay as a new screening tool for toxic chemicals

NASA Astrophysics Data System (ADS)

Moczko, Ewa; Mirkes, Evgeny M.; Cáceres, César; Gorban, Alexander N.; Piletsky, Sergey

2016-09-01

Our study involves development of fluorescent cell-based diagnostic assay as a new approach in high-throughput screening method. This highly sensitive optical assay operates similarly to e-noses and e-tongues which combine semi-specific sensors and multivariate data analysis for monitoring biochemical processes. The optical assay consists of a mixture of environmental-sensitive fluorescent dyes and human skin cells that generate fluorescence spectra patterns distinctive for particular physico-chemical and physiological conditions. Using chemometric techniques the optical signal is processed providing qualitative information about analytical characteristics of the samples. This integrated approach has been successfully applied (with sensitivity of 93% and specificity of 97%) in assessing whether particular chemical agents are irritating or not for human skin. It has several advantages compared with traditional biochemical or biological assays and can impact the new way of high-throughput screening and understanding cell activity. It also can provide reliable and reproducible method for assessing a risk of exposing people to different harmful substances, identification active compounds in toxicity screening and safety assessment of drugs, cosmetic or their specific ingredients.

Investigation of drug-excipient compatibility using rheological and thermal tools

NASA Astrophysics Data System (ADS)

Trivedi, Maitri R.

HYPOTHESIS: We plan to investigate a different approach to evaluate drug-excipient physical compatibility using rheological and thermal tools as opposed to commonly used chemical techniques in pharmaceutical industry. This approach offers practical solutions to routinely associated problems arising with API's and commonly used hydrates forms of excipients. ABSTRACT: Drug-Excipient compatibility studies are an important aspect of pre-formulation and formulation development in pharmaceutical research and development. Various approaches have been used in pharmaceutical industry including use of thermal analysis and quantitative assessment of drug-excipient mixtures after keeping the samples under stress environment depending upon the type of formulation. In an attempt to provide better understanding of such compatibility aspect of excipients with different properties of API, various rheological and thermal studies were conducted on binary mixtures of excipients which exist in different hydrates. Dibasic Calcium Phosphate (DCP, anhydrous and dihydrate forms) and Lactose (Lac, anhydrous and monohydrate) were selected with cohesive API's (Acetaminophen and Aspirin). Binary mixtures of DCP and Lac were prepared by addition of 0% w/w to 50% w/w of the API into each powder blend. Rheological and thermal aspects were considered using different approaches such as powder rheometer, rotational shear cell and traditional rheometery approaches like angle of repose (AOR), hausner's ratio (HR) and cares index (CI). Thermal analysis was conducted using modulated differential scanning calorimetry (MDSC) and thermal effusivity. The data suggested that the powder rheometer showed distinctive understanding in the flowability behavior of binary mixtures with addition of increasing proportion of API's than traditional approaches. Thermal approaches revealed the potential interaction of water of crystallization DCP-D with the API (APAP) while such interactions were absent in DCP-A, while in case of Lac-M and Lac-A, interaction with water of crystallization were not present. Binary mixtures prepared with DCP-D were better flowable while blends with DCP-A were better in stability (physical), compressibility and permeability. Similarly binary mixtures prepared with Lac-M were better flowable and stable in physical compatibility as compared to Lac-A. Lac-A were better in compressibility and permeability. Second part of these research included understanding the powder behavior from wet granulation point of view. Wet granulation includes the formation of agglomerates with powders to form granules in order to have better flowability, content uniformity and compressibility of granular mass. End point determination of powders involving change in powder energies and compressibility, permeability along with thermal analyses were conducted. The effects of water of crystallization on end point determination was studied and based on which overall effects on drug-excipient compatibility using different hydrate forms of excipients were evaluated.

A Combined Kinetic and Volatility Basis Set Approach to Model Secondary Organic Aerosol from Toluene and Diesel Exhaust/Meat Cooking Mixtures

NASA Astrophysics Data System (ADS)

Parikh, H. M.; Carlton, A. G.; Zhang, H.; Kamens, R.; Vizuete, W.

2011-12-01

Secondary organic aerosol (SOA) is simulated for 6 outdoor smog chamber experiments using a SOA model based on a kinetic chemical mechanism in conjunction with a volatility basis set (VBS) approach. The experiments include toluene, a non-SOA-forming hydrocarbon mixture, diesel exhaust or meat cooking emissions and NOx, and are performed under varying conditions of relative humidity. SOA formation from toluene is modeled using a condensed kinetic aromatic mechanism that includes partitioning of lumped semi-volatile products in particle organic-phase and incorporates particle aqueous-phase chemistry to describe uptake of glyoxal and methylglyoxal. Modeling using the kinetic mechanism alone, along with primary organic aerosol (POA) from diesel exhaust (DE) /meat cooking (MC) fails to simulate the rapid SOA formation at the beginning hours of the experiments. Inclusion of a VBS approach with the kinetic mechanism to characterize the emissions and chemistry of complex mixture of intermediate volatility organic compounds (IVOCs) from DE/MC, substantially improves SOA predictions when compared with observed data. The VBS model includes photochemical aging of IVOCs and evaporation of POA after dilution. The relative contribution of SOA mass from DE/MC is as high as 95% in the morning, but substantially decreases after mid-afternoon. For high humidity experiments, aqueous-phase SOA fraction dominates the total SOA mass at the end of the day (approximately 50%). In summary, the combined kinetic and VBS approach provides a new and improved framework to semi-explicitly model SOA from VOC precursors in conjunction with a VBS approach that can be used on complex emission mixtures comprised with hundreds of individual chemical species.

Flow behaviour and structure of heterogeneous particles-water mixture in horizontal and inclined pipes

NASA Astrophysics Data System (ADS)

Vlasák, Pavel; Chára, Zdeněk; Konfršt, Jiří

2018-06-01

The effect of slurry velocity and mean concentration of heterogeneous particle-water mixture on flow behaviour and structure in the turbulent regime was studied in horizontal and inclined pipe sections of inner diameter D = 100 mm. The stratified flow pattern of heterogeneous particle-water mixture in the inclined pipe sections was revealed. The particles moved mostly near to the pipe invert. Concentration distribution in ascending and descending vertical pipe sections confirmed the effect of fall velocity on particle-carrier liquid slip velocity and increase of in situ concentration in the ascending pipe section. Slip velocity in two-phase flow, which is defined as the velocity difference between the solid and liquid phase, is one of mechanism of particle movement in two-phase flow. Due to the slip velocity, there is difference between transport and in situ concentrations, and the slip velocity can be determined from comparison of the in situ and transport concentration. For heterogeneous particle-water mixture flow the slip velocity depends on the flow structure.

Non-Genomic Effects of Xenoestrogen Mixtures

PubMed Central

Viñas, René; Jeng, Yow-Jiun; Watson, Cheryl S.

2012-01-01

Xenoestrogens (XEs) are chemicals derived from a variety of natural and anthropogenic sources that can interfere with endogenous estrogens by either mimicking or blocking their responses via non-genomic and/or genomic signaling mechanisms. Disruption of estrogens’ actions through the less-studied non-genomic pathway can alter such functional end points as cell proliferation, peptide hormone release, catecholamine transport, and apoptosis, among others. Studies of potentially adverse effects due to mixtures and to low doses of endocrine-disrupting chemicals have recently become more feasible, though few so far have included actions via the non-genomic pathway. Physiologic estrogens and XEs evoke non-monotonic dose responses, with different compounds having different patterns of actions dependent on concentration and time, making mixture assessments all the more challenging. In order to understand the spectrum of toxicities and their mechanisms, future work should focus on carefully studying individual and mixture components across a range of concentrations and cellular pathways in a variety of tissue types. PMID:23066391

Effects of alkyl chain length and substituent pattern of fullerene bis-adducts on film structures and photovoltaic properties of bulk heterojunction solar cells.

PubMed

Tao, Ran; Umeyama, Tomokazu; Kurotobi, Kei; Imahori, Hiroshi

2014-10-08

A series of alkoxycarbonyl-substituted dihydronaphthyl-based [60]fullerene bis-adduct derivatives (denoted as C2BA, C4BA, and C6BA with the alkyl chain of ethyl, n-butyl, and n-hexyl, respectively) have been synthesized to investigate the effects of alkyl chain length and substituent pattern of fullerene bis-adducts on the film structures and photovoltaic properties of bulk heterojunction polymer solar cells. The shorter alkyl chain length caused lower solubility of the fullerene bis-adducts (C6BA > C4BA > C2BA), thereby resulting in the increased separation difficulty of respective bis-adduct isomers. The device performance based on poly(3-hexylthiophene) (P3HT) and the fullerene bis-adduct regioisomer mixtures was enhanced by shortening the alkyl chain length. When using the regioisomerically separated fullerene bis-adducts, the devices based on trans-2 and a mixture of trans-4 and e of C4BA exhibited the highest power conversion efficiencies of ca. 2.4%, which are considerably higher than those of the C6BA counterparts (ca. 1.4%) and the C4BA regioisomer mixture (1.10%). The film morphologies as well as electron mobilities of the P3HT:bis-adduct blend films were found to affect the photovoltaic properties considerably. These results reveal that the alkyl chain length and substituent pattern of fullerene bis-adducts significantly influence the photovoltaic properties as well as the film structures of bulk heterojunction solar cells.

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

MALDI-MS SCREENING FOR PSEUDOURIDINE IN MIXTURES OF SMALL RNAS BY CHEMICAL DERIVATIZATION, RNASE DIGESTION AND SIGNATURE PRODUCTS

PubMed Central

Durairaj, Anita; Limbach, Patrick A.

2010-01-01

We have developed a method to screen for pseudouridines in complex mixtures of small RNAs using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS). First, the unfractionated crude mixture of tRNAs is digested to completion with an endoribonuclease, such as RNase T1, and the digestion products are examined using MALDI-MS. Individual RNAs are identified by their signature digestion products, which arise through the detection of unique mass values after nuclease digestion. Next, the endonuclease digest is derivatized using N-cyclohexyl-N’-(2-morpholinoethyl)-carbodiimide metho-p-toluenesulfonate (CMCT), which selectively modifies all pseudouridine, thiouridine and 2-methylthio-6-isopentenyladenosine nucleosides. MALDI-MS determination of the CMCT-derivatized endonuclease digest reveals the presence of pseudouridine through a 252 Da mass increase over the underivatized digest. Proof-of-concept experiments were conducted using a mixture of Escherichia coli transfer RNAs and endoribonucleases T1 and A. More than 80% of the expected pseudouridines from this mixture were detected using this screening approach, even on a unfractionated sample of tRNAs. This approach should be particularly useful in the identification of putative pseudouridine synthases through detection of their target RNAs and can provide insight into specific small RNAs that may contain pseudouridine. PMID:18973194

Examining the effect of initialization strategies on the performance of Gaussian mixture modeling.

PubMed

Shireman, Emilie; Steinley, Douglas; Brusco, Michael J

2017-02-01

Mixture modeling is a popular technique for identifying unobserved subpopulations (e.g., components) within a data set, with Gaussian (normal) mixture modeling being the form most widely used. Generally, the parameters of these Gaussian mixtures cannot be estimated in closed form, so estimates are typically obtained via an iterative process. The most common estimation procedure is maximum likelihood via the expectation-maximization (EM) algorithm. Like many approaches for identifying subpopulations, finite mixture modeling can suffer from locally optimal solutions, and the final parameter estimates are dependent on the initial starting values of the EM algorithm. Initial values have been shown to significantly impact the quality of the solution, and researchers have proposed several approaches for selecting the set of starting values. Five techniques for obtaining starting values that are implemented in popular software packages are compared. Their performances are assessed in terms of the following four measures: (1) the ability to find the best observed solution, (2) settling on a solution that classifies observations correctly, (3) the number of local solutions found by each technique, and (4) the speed at which the start values are obtained. On the basis of these results, a set of recommendations is provided to the user.

Conceptual design of distillation-based hybrid separation processes.

PubMed

Skiborowski, Mirko; Harwardt, Andreas; Marquardt, Wolfgang

2013-01-01

Hybrid separation processes combine different separation principles and constitute a promising design option for the separation of complex mixtures. Particularly, the integration of distillation with other unit operations can significantly improve the separation of close-boiling or azeotropic mixtures. Although the design of single-unit operations is well understood and supported by computational methods, the optimal design of flowsheets of hybrid separation processes is still a challenging task. The large number of operational and design degrees of freedom requires a systematic and optimization-based design approach. To this end, a structured approach, the so-called process synthesis framework, is proposed. This article reviews available computational methods for the conceptual design of distillation-based hybrid processes for the separation of liquid mixtures. Open problems are identified that must be addressed to finally establish a structured process synthesis framework for such processes.

A Greener Arctic: Vascular Plant Litter Input in Subarctic Peat Bogs Changes Soil Invertebrate Diets and Decomposition Patterns

NASA Astrophysics Data System (ADS)

Krab, E. J.; Berg, M. P.; Aerts, R.; van Logtestijn, R. S. P.; Cornelissen, H. H. C.

2014-12-01

Climate-change-induced trends towards shrub dominance in subarctic, moss-dominated peatlands will most likely have large effects on soil carbon (C) dynamics through an input of more easily decomposable litter. The mechanisms by which this increase in vascular litter input interacts with the abundance and diet-choice of the decomposer community to alter C-processing have, however, not yet been unraveled. We used a novel 13C tracer approach to link invertebrate species composition (Collembola), abundance and species-specific feeding behavior to C-processing of vascular and peat moss litters. We incubated different litter mixtures, 100% Sphagnum moss litter, 100% Betula leaf litter, and a 50/50 mixture of both, in mesocosms for 406 days. We revealed the transfer of C from the litters to the soil invertebrate species by 13C labeling of each of the litter types and assessed 13C signatures of the invertebrates Collembola species composition differed significantly between Sphagnum and Betula litter. Within the 'single type litter' mesocosms, Collembola species showed different 13C signatures, implying species-specific differences in diet choice. Surprisingly, the species composition and Collembola abundance changed relatively little as a consequence of Betula input to a Sphagnum based system. Their diet choice, however, changed drastically; species-specific differences in diet choice disappeared and approximately 67% of the food ingested by all Collembola originated from Betula litter. Furthermore, litter decomposition patterns corresponded to these findings; mass loss of Betula increased from 16.1% to 26.2% when decomposing in combination with Sphagnum, while Sphagnum decomposed even slower in combination with Betula litter (1.9%) than alone (4.7%). This study is the first to empirically show that collective diet shifts of the peatland decomposer community from mosses towards vascular plant litter may drive altered decomposition patterns. In addition, we showed that although species-specific differences in Collembola feeding behavior appear to exist, species are very plastic in their diet. This implies that changes in C turnover rates with vegetation shifts, might well be due to diet shifts of the present decomposer community rather than by changes in species composition.

Application of imaging technology to improve the laboratory and field compaction of HMA.

DOT National Transportation Integrated Search

2009-04-01

Field compaction of asphalt mixtures is an important process that influences performance of asphalt : pavements. This study evaluates the relationship between different field compaction patterns and the : uniformity of air void distribution in asphal...

Velocity field measurements in tailings dam failure experiments using a combined PIV-PTV approach

USDA-ARS?s Scientific Manuscript database

Tailings dams are built to impound mining waste, also called tailings, which consists of a mixture of fine-sized sediments and water contaminated with some hazardous chemicals used for extracting the ore by leaching. Non-Newtonian flow of sediment-water mixture resulting from a failure of tailings d...

QUANTIFYING THE EFFECTS OF THE MIXING PROCESS IN FABRICATED DILUTION SYSTEMS ON PARTICULATE EMISSION MEASUREMENTS VIA AN INTEGRATED EXPERIMENTAL AND MODELING APPROACH

EPA Science Inventory

Structuring Cooperative Learning for Motivation and Conceptual Change in the Concepts of Mixtures

ERIC Educational Resources Information Center

Belge Can, Hatice; Boz, Yezdan

2016-01-01

This study investigates the effect of structuring cooperative learning based on conceptual change approach on grade 9 students' understanding the concepts of mixtures and their motivation, compared with traditional instruction. Among six classes of a high school, two of them were randomly assigned to cooperative learning group where students were…

A MIXTURE OF SEVEN ANTIANDROGENIC COMPOUNDS ELICITS ADDITIVE EFFECTS ON THE MALE RAT REPRODUCTIVE TRACT THAT CORRESPOND TO MODELED PREDICTIONS

EPA Science Inventory

The main objectives of this study were to: (1) determine whether dissimilar antiandrogenic compounds display additive effects when present in combination and (2) to assess the ability of modelling approaches to accurately predict these mixture effects based on data from single ch...

PROCEDURES FOR DERIVING EQUILIBRIUM PARTITIONING SEDIMENT BENCHMARKS (ESBS) FOR THE PROTECTION OF BENTHIC ORGANISMS: METALS MIXTURES (CADMIUM, COPPER, LEAD, NICKEL, SILVER, AND ZINC)

EPA Science Inventory

This equilibrium partitioning sediment benchmark (ESB) document describes procedures to derive concentrations of metal mixtures in sediment which are protective of the presence of benthic organisms. The equilibrium partitioning (EqP) approach was chosen because it accounts for t...

Behavioural and biochemical responses to metals tested alone or in mixture (Cd-Cu-Ni-Pb-Zn) in Gammarus fossarum: From a multi-biomarker approach to modelling metal mixture toxicity.

PubMed

Lebrun, Jérémie D; Uher, Emmanuelle; Fechner, Lise C

2017-12-01

Metals are usually present as mixtures at low concentrations in aquatic ecosystems. However, the toxicity and sub-lethal effects of metal mixtures on organisms are still poorly addressed in environmental risk assessment. Here we investigated the biochemical and behavioural responses of Gammarus fossarum to Cu, Cd, Ni, Pb and Zn tested individually or in mixture (M2X) at concentrations twice the levels of environmental quality standards (EQSs) from the European Water Framework Directive. The same metal mixture was also tested with concentrations equivalent to EQSs (M1X), thus in a regulatory context, as EQSs are proposed to protect aquatic biota. For each exposure condition, mortality, locomotion, respiration and enzymatic activities involved in digestive metabolism and moult were monitored over a 120h exposure period. Multi-metric variations were summarized by the integrated biomarker response index (IBR). Mono-metallic exposures shed light on biological alterations occurring at environmental exposure levels in gammarids and depending on the considered metal and gender. As regards mixtures, biomarkers were altered for both M2X and M1X. However, no additive or synergistic effect of metals was observed comparing to mono-metallic exposures. Indeed, bioaccumulation data highlighted competitive interactions between metals in M2X, decreasing subsequently their internalisation and toxicity. IBR values indicated that the health of gammarids was more impacted by M1X than M2X, because of reduced competitions and enhanced uptakes of metals for the mixture at lower, EQS-like concentrations. Models using bioconcentration data obtained from mono-metallic exposures generated successful predictions of global toxicity both for M1X and M2X. We conclude that sub-lethal effects of mixtures identified by the multi-biomarker approach can lead to disturbances in population dynamics of gammarids. Although IBR-based models offer promising lines of enquiry to predict metal mixture toxicity, further studies are needed to confirm their predictive quality on larger ranges of metallic combinations before their use in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Enzyme-coupled nanoparticles-assisted laser desorption ionization mass spectrometry for searching for low-mass inhibitors of enzymes in complex mixtures.

PubMed

Salwiński, Aleksander; Da Silva, David; Delépée, Raphaël; Maunit, Benoît

2014-04-01

In this report, enzyme-coupled magnetic nanoparticles (EMPs) were shown to be an effective affinity-based tool for finding specific interactions between enzymatic targets and the low-mass molecules in complex mixtures using classic MALDI-TOF apparatus. EMPs used in this work act as nonorganic matrix enabling ionization of small molecules without any interference in the low-mass range (enzyme-coupled nanoparticles-assisted laser desorption ionization MS, ENALDI MS) and simultaneously carry the superficial specific binding sites to capture inhibitors present in a studied mixture. We evaluated ENALDI approach in two complementary variations: 'ion fading' (IF-ENALDI), based on superficial adsorption of inhibitors and 'ion hunting' (IH-ENALDI), based on selective pre-concentration of inhibitors. IF-ENALDI was applied for two sets of enzyme-inhibitor pairs: tyrosinase-glabridin and trypsin-leupeptin and for the real plant sample: Sparrmannia discolor leaf and stem methanol extract. The efficacy of IH-ENALDI was shown for the pair of trypsin-leupeptin. Both ENALDI approaches pose an alternative for bioassay-guided fractionation, the common method for finding inhibitors in the complex mixtures.

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.

Machine-learned analysis of quantitative sensory testing responses to noxious cold stimulation in healthy subjects.

PubMed

Weyer-Menkhoff, I; Thrun, M C; Lötsch, J

2018-05-01

Pain in response to noxious cold has a complex molecular background probably involving several types of sensors. A recent observation has been the multimodal distribution of human cold pain thresholds. This study aimed at analysing reproducibility and stability of this observation and further exploration of data patterns supporting a complex background. Pain thresholds to noxious cold stimuli (range 32-0 °C, tonic: temperature decrease -1 °C/s, phasic: temperature decrease -8 °C/s) were acquired in 148 healthy volunteers. The probability density distribution was analysed using machine-learning derived methods implemented as Gaussian mixture modeling (GMM), emergent self-organizing maps and self-organizing swarms of data agents. The probability density function of pain responses was trimodal (mean thresholds at 25.9, 18.4 and 8.0 °C for tonic and 24.5, 18.1 and 7.5 °C for phasic stimuli). Subjects' association with Gaussian modes was consistent between both types of stimuli (weighted Cohen's κ = 0.91). Patterns emerging in self-organizing neuronal maps and swarms could be associated with different trends towards decreasing cold pain sensitivity in different Gaussian modes. On self-organizing maps, the third Gaussian mode emerged as particularly distinct. Thresholds at, roughly, 25 and 18 °C agree with known working temperatures of TRPM8 and TRPA1 ion channels, respectively, and hint at relative local dominance of either channel in respective subjects. Data patterns suggest involvement of further distinct mechanisms in cold pain perception at lower temperatures. Findings support data science approaches to identify biologically plausible hints at complex molecular mechanisms underlying human pain phenotypes. Sensitivity to pain is heterogeneous. Data-driven computational research approaches allow the identification of subgroups of subjects with a distinct pattern of sensitivity to cold stimuli. The subgroups are reproducible with different types of noxious cold stimuli. Subgroups show pattern that hints at distinct and inter-individually different types of the underlying molecular background. © 2018 European Pain Federation - EFIC®.

A Bayesian model for time-to-event data with informative censoring

PubMed Central

Kaciroti, Niko A.; Raghunathan, Trivellore E.; Taylor, Jeremy M. G.; Julius, Stevo

2012-01-01

Randomized trials with dropouts or censored data and discrete time-to-event type outcomes are frequently analyzed using the Kaplan–Meier or product limit (PL) estimation method. However, the PL method assumes that the censoring mechanism is noninformative and when this assumption is violated, the inferences may not be valid. We propose an expanded PL method using a Bayesian framework to incorporate informative censoring mechanism and perform sensitivity analysis on estimates of the cumulative incidence curves. The expanded method uses a model, which can be viewed as a pattern mixture model, where odds for having an event during the follow-up interval (tk−1,tk], conditional on being at risk at tk−1, differ across the patterns of missing data. The sensitivity parameters relate the odds of an event, between subjects from a missing-data pattern with the observed subjects for each interval. The large number of the sensitivity parameters is reduced by considering them as random and assumed to follow a log-normal distribution with prespecified mean and variance. Then we vary the mean and variance to explore sensitivity of inferences. The missing at random (MAR) mechanism is a special case of the expanded model, thus allowing exploration of the sensitivity to inferences as departures from the inferences under the MAR assumption. The proposed approach is applied to data from the TRial Of Preventing HYpertension. PMID:22223746

Isolation and genetic analysis of pure cells from forensic biological mixtures: The precision of a digital approach.

PubMed

Fontana, F; Rapone, C; Bregola, G; Aversa, R; de Meo, A; Signorini, G; Sergio, M; Ferrarini, A; Lanzellotto, R; Medoro, G; Giorgini, G; Manaresi, N; Berti, A

2017-07-01

Latest genotyping technologies allow to achieve a reliable genetic profile for the offender identification even from extremely minute biological evidence. The ultimate challenge occurs when genetic profiles need to be retrieved from a mixture, which is composed of biological material from two or more individuals. In this case, DNA profiling will often result in a complex genetic profile, which is then subject matter for statistical analysis. In principle, when more individuals contribute to a mixture with different biological fluids, their single genetic profiles can be obtained by separating the distinct cell types (e.g. epithelial cells, blood cells, sperm), prior to genotyping. Different approaches have been investigated for this purpose, such as fluorescent-activated cell sorting (FACS) or laser capture microdissection (LCM), but currently none of these methods can guarantee the complete separation of different type of cells present in a mixture. In other fields of application, such as oncology, DEPArray™ technology, an image-based, microfluidic digital sorter, has been widely proven to enable the separation of pure cells, with single-cell precision. This study investigates the applicability of DEPArray™ technology to forensic samples analysis, focusing on the resolution of the forensic mixture problem. For the first time, we report here the development of an application-specific DEPArray™ workflow enabling the detection and recovery of pure homogeneous cell pools from simulated blood/saliva and semen/saliva mixtures, providing full genetic match with genetic profiles of corresponding donors. In addition, we assess the performance of standard forensic methods for DNA quantitation and genotyping on low-count, DEPArray™-isolated cells, showing that pure, almost complete profiles can be obtained from as few as ten haploid cells. Finally, we explore the applicability in real casework samples, demonstrating that the described approach provides complete separation of cells with outstanding precision. In all examined cases, DEPArray™ technology proves to be a groundbreaking technology for the resolution of forensic biological mixtures, through the precise isolation of pure cells for an incontrovertible attribution of the obtained genetic profiles. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Transport properties of mixtures by the soft-SAFT + free-volume theory: application to mixtures of n-alkanes and hydrofluorocarbons.

PubMed

Llovell, F; Marcos, R M; Vega, L F

2013-05-02

In a previous paper (Llovell et al. J. Phys. Chem. B, submitted for publication), the free-volume theory (FVT) was coupled with the soft-SAFT equation of state for the first time to extend the capabilities of the equation to the calculation of transport properties. The equation was tested with molecular simulations and applied to the family of n-alkanes. The capability of the soft-SAFT + FVT treatment is extended here to other chemical families and mixtures. The compositional rules of Wilke (Wilke, C. R. J. Chem. Phys. 1950, 18, 517-519) are used for the diluted term of the viscosity, while the dense term is evaluated using very simple mixing rules to calculate the viscosity parameters. The theory is then used to predict the vapor-liquid equilibrium and the viscosity of mixtures of nonassociating and associating compounds. The approach is applied to determine the viscosity of a selected group of hydrofluorocarbons, in a similar manner as previously done for n-alkanes. The soft-SAFT molecular parameters are taken from a previous work, fitted to vapor-liquid equilibria experimental data. The application of FVT requires three additional parameters related to the viscosity of the pure fluid. Using a transferable approach, the α parameter is taken from the equivalent n-alkane, while the remaining two parameters B and Lv are fitted to viscosity data of the pure fluid at several isobars. The effect of these parameters is then investigated and compared to those obtained for n-alkanes, in order to better understand their effect on the calculations. Once the pure fluids are well characterized, the vapor-liquid equilibrium and the viscosity of nonassociating and associating mixtures, including n-alkane + n-alkane, hydrofluorocarbon + hydrofluorocarbon, and n-alkane + hydrofluorocarbon mixtures, are calculated. One or two binary parameters are used to account for deviations in the vapor-liquid equilibrium diagram for nonideal mixtures; these parameters are used in a transferable manner to predict the viscosity of the mixtures. Very good agreement with available experimental data is found in all cases, with an average absolute deviation ranging between 1.0% and 5.5%, even when the system presents azeotropy, reinforcing the robustness of the approach.

NASA's Software Bank (NETS)

NASA Technical Reports Server (NTRS)

1992-01-01

NETS (A Neural Network Development Tool) is a software system for mimicking the human brain. It is used in a University of Arkansas project in pattern matching of chemical systems. If successful, chemists would be able to identify mixtures of compounds without long and costly separation procedures. Using NETS, the group has trained the computer to recognize pattern relationships in a known compound and associate the results to an unknown compound. The research appears to be promising.

Microchemical Systems and Their Applications Workshop Held on 16-18 June 1999 in Reston, Virginia

DTIC Science & Technology

2000-03-29

USABLE BY- PRODUCT HYDROGEN, BUT COST OF THE PT COATED CERAMIC TUBES IS HIGH, HEAT TRANSFER EFFICIENCY IS LIMITED, AND THE RISK ASSOCIATED WITH...Monolith reactor Monolith Catalyst A Gas mixture i quartz tube T 1 Radiation Shields GC / analysis 3M Monolith Catalysts *-v.V...polyamide. MicroChannel patterned laminates are fabricated from polyamide while microfin -patterned laminates are fabricated from copper. In addition to

Geometrical Patterning of Super-Hydrophobic Biosensing Transistors Enables Space and Time Resolved Analysis of Biological Mixtures.

PubMed

Gentile, Francesco; Ferrara, Lorenzo; Villani, Marco; Bettelli, Manuele; Iannotta, Salvatore; Zappettini, Andrea; Cesarelli, Mario; Di Fabrizio, Enzo; Coppedè, Nicola

2016-01-12

PSS is a conductive polymer that can be integrated into last generation Organic Electrochemical Transistor (OECT) devices for biological inspection, identification and analysis. While a variety of reports in literature demonstrated the chemical and biological sensitivity of these devices, still their ability in resolving complex mixtures remains controversial. Similar OECT devices display good time dynamics behavior but lack spatial resolution. In this work, we integrated PSS with patterns of super-hydrophobic pillars in which a finite number of those pillars is independently controlled for site-selective measurement of a solution. We obtained a multifunctional, hierarchical OECT device that bridges the micro- to the nano-scales for specific, combined time and space resolved analysis of the sample. Due to super-hydrophobic surface properties, the biological species in the drop are driven by convection, diffusion, and the externally applied electric field: the balance/unbalance between these forces will cause the molecules to be transported differently within its volume depending on particle size thus realizing a size-selective separation. Within this framework, the separation and identification of two different molecules, namely Cetyl Trimethyl Ammonium Bromid (CTAB) and adrenaline, in a biological mixture have been demonstrated, showing that geometrical control at the micro-nano scale impart unprecedented selectivity to the devices.

Geometrical Patterning of Super-Hydrophobic Biosensing Transistors Enables Space and Time Resolved Analysis of Biological Mixtures

PubMed Central

Gentile, Francesco; Ferrara, Lorenzo; Villani, Marco; Bettelli, Manuele; Iannotta, Salvatore; Zappettini, Andrea; Cesarelli, Mario; Di Fabrizio, Enzo; Coppedè, Nicola

2016-01-01

PEDOT:PSS is a conductive polymer that can be integrated into last generation Organic Electrochemical Transistor (OECT) devices for biological inspection, identification and analysis. While a variety of reports in literature demonstrated the chemical and biological sensitivity of these devices, still their ability in resolving complex mixtures remains controversial. Similar OECT devices display good time dynamics behavior but lack spatial resolution. In this work, we integrated PEDOT:PSS with patterns of super-hydrophobic pillars in which a finite number of those pillars is independently controlled for site-selective measurement of a solution. We obtained a multifunctional, hierarchical OECT device that bridges the micro- to the nano-scales for specific, combined time and space resolved analysis of the sample. Due to super-hydrophobic surface properties, the biological species in the drop are driven by convection, diffusion, and the externally applied electric field: the balance/unbalance between these forces will cause the molecules to be transported differently within its volume depending on particle size thus realizing a size-selective separation. Within this framework, the separation and identification of two different molecules, namely Cetyl Trimethyl Ammonium Bromid (CTAB) and adrenaline, in a biological mixture have been demonstrated, showing that geometrical control at the micro-nano scale impart unprecedented selectivity to the devices. PMID:26753611

Geometrical Patterning of Super-Hydrophobic Biosensing Transistors Enables Space and Time Resolved Analysis of Biological Mixtures

NASA Astrophysics Data System (ADS)

Gentile, Francesco; Ferrara, Lorenzo; Villani, Marco; Bettelli, Manuele; Iannotta, Salvatore; Zappettini, Andrea; Cesarelli, Mario; di Fabrizio, Enzo; Coppedè, Nicola

2016-01-01

PEDOT:PSS is a conductive polymer that can be integrated into last generation Organic Electrochemical Transistor (OECT) devices for biological inspection, identification and analysis. While a variety of reports in literature demonstrated the chemical and biological sensitivity of these devices, still their ability in resolving complex mixtures remains controversial. Similar OECT devices display good time dynamics behavior but lack spatial resolution. In this work, we integrated PEDOT:PSS with patterns of super-hydrophobic pillars in which a finite number of those pillars is independently controlled for site-selective measurement of a solution. We obtained a multifunctional, hierarchical OECT device that bridges the micro- to the nano-scales for specific, combined time and space resolved analysis of the sample. Due to super-hydrophobic surface properties, the biological species in the drop are driven by convection, diffusion, and the externally applied electric field: the balance/unbalance between these forces will cause the molecules to be transported differently within its volume depending on particle size thus realizing a size-selective separation. Within this framework, the separation and identification of two different molecules, namely Cetyl Trimethyl Ammonium Bromid (CTAB) and adrenaline, in a biological mixture have been demonstrated, showing that geometrical control at the micro-nano scale impart unprecedented selectivity to the devices.

Organic synthesis in experimental impact shocks

NASA Technical Reports Server (NTRS)

McKay, C. P.; Borucki, W. J.

1997-01-01

Laboratory simulations of shocks created with a high-energy laser demonstrate that the efficacy of organic production depends on the molecular, not just the elemental composition of the shocked gas. In a methane-rich mixture that simulates a low-temperature equilibrium mixture of cometary material, hydrogen cyanide and acetylene were produced with yields of 5 x 10(17) molecules per joule. Repeated shocking of the methane-rich mixture produced amine groups, suggesting the possible synthesis of amino acids. No organic molecules were produced in a carbon dioxide-rich mixture, which is at odds with thermodynamic equilibrium approaches to shock chemistry and has implications for the modeling of shock-produced organic molecules on early Earth.

Methods and apparatuses for making cathodes for high-temperature, rechargeable batteries

DOEpatents

Meinhardt, Kerry D; Sprenkle, Vincent L; Coffey, Gregory W

2014-05-20

The approaches for fabricating cathodes can be adapted to improve control over cathode composition and to better accommodate batteries of any shape and their assembly. For example, a first solid having an alkali metal halide, a second solid having a transition metal, and a third solid having an alkali metal aluminum halide are combined into a mixture. The mixture can be heated in a vacuum to a temperature that is greater than or equal to the melting point of the third solid. When the third solid is substantially molten liquid, the mixture is compressed into a desired cathode shape and then cooled to solidify the mixture in the desired cathode shape.

Apparatuses for making cathodes for high-temperature, rechargeable batteries

DOEpatents

Meinhardt, Kerry D.; Sprenkle, Vincent L.; Coffey, Gregory W.

2016-09-13

The approaches and apparatuses for fabricating cathodes can be adapted to improve control over cathode composition and to better accommodate batteries of any shape and their assembly. For example, a first solid having an alkali metal halide, a second solid having a transition metal, and a third solid having an alkali metal aluminum halide are combined into a mixture. The mixture can be heated in a vacuum to a temperature that is greater than or equal to the melting point of the third solid. When the third solid is substantially molten liquid, the mixture is compressed into a desired cathode shape and then cooled to solidify the mixture in the desired cathode shape.

Minimization of required model runs in the Random Mixing approach to inverse groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Hoerning, Sebastian; Bardossy, Andras; du Plessis, Jaco

2017-04-01

Most geostatistical inverse groundwater flow and transport modelling approaches utilize a numerical solver to minimize the discrepancy between observed and simulated hydraulic heads and/or hydraulic concentration values. The optimization procedure often requires many model runs, which for complex models lead to long run times. Random Mixing is a promising new geostatistical technique for inverse modelling. The method is an extension of the gradual deformation approach. It works by finding a field which preserves the covariance structure and maintains observed hydraulic conductivities. This field is perturbed by mixing it with new fields that fulfill the homogeneous conditions. This mixing is expressed as an optimization problem which aims to minimize the difference between the observed and simulated hydraulic heads and/or concentration values. To preserve the spatial structure, the mixing weights must lie on the unit hyper-sphere. We present a modification to the Random Mixing algorithm which significantly reduces the number of model runs required. The approach involves taking n equally spaced points on the unit circle as weights for mixing conditional random fields. Each of these mixtures provides a solution to the forward model at the conditioning locations. For each of the locations the solutions are then interpolated around the circle to provide solutions for additional mixing weights at very low computational cost. The interpolated solutions are used to search for a mixture which maximally reduces the objective function. This is in contrast to other approaches which evaluate the objective function for the n mixtures and then interpolate the obtained values. Keeping the mixture on the unit circle makes it easy to generate equidistant sampling points in the space; however, this means that only two fields are mixed at a time. Once the optimal mixture for two fields has been found, they are combined to form the input to the next iteration of the algorithm. This process is repeated until a threshold in the objective function is met or insufficient changes are produced in successive iterations.

Field applications of stand-off sensing using visible/NIR multivariate optical computing

NASA Astrophysics Data System (ADS)

Eastwood, DeLyle; Soyemi, Olusola O.; Karunamuni, Jeevanandra; Zhang, Lixia; Li, Hongli; Myrick, Michael L.

2001-02-01

12 A novel multivariate visible/NIR optical computing approach applicable to standoff sensing will be demonstrated with porphyrin mixtures as examples. The ultimate goal is to develop environmental or counter-terrorism sensors for chemicals such as organophosphorus (OP) pesticides or chemical warfare simulants in the near infrared spectral region. The mathematical operation that characterizes prediction of properties via regression from optical spectra is a calculation of inner products between the spectrum and the pre-determined regression vector. The result is scaled appropriately and offset to correspond to the basis from which the regression vector is derived. The process involves collecting spectroscopic data and synthesizing a multivariate vector using a pattern recognition method. Then, an interference coating is designed that reproduces the pattern of the multivariate vector in its transmission or reflection spectrum, and appropriate interference filters are fabricated. High and low refractive index materials such as Nb2O5 and SiO2 are excellent choices for the visible and near infrared regions. The proof of concept has now been established for this system in the visible and will later be extended to chemicals such as OP compounds in the near and mid-infrared.

Heterogeneity in perinatal depression: how far have we come? A systematic review.

PubMed

Santos, Hudson; Tan, Xianming; Salomon, Rebecca

2017-02-01

Despite perinatal depression (PND) being a common mental disorder affecting pregnant women and new mothers, limited attention has been paid to the heterogeneous nature of this disorder. We examined heterogeneity in PND symptom profiles and symptom trajectories. Literature searches revealed 247 studies, 23 of which were included in the final review. The most common statistical approaches used to explore symptom and trajectory heterogeneity were latent class model and growth mixture model. All but one study examined PND symptom trajectories and provided collective evidence of at least three heterogeneous patterns: low, medium, or chronic-high symptom levels. Social and psychological risk factors were the most common group of predictors related to a higher burden (high sum of score) of depressive symptoms. These studies were consistent in reporting poorer health outcomes for children of mothers assigned to high burden symptom trajectories. Only one study explored heterogeneity in symptom profile and was the only one to describe the specific constellations of depressive symptoms related to the PND heterogeneous patterns identified. Therefore, there is limited evidence on the specific symptoms and symptom configurations that make up PND heterogeneity. We suggest directions for future research to further clarify the PND heterogeneity and its related mechanisms.

An approach toward quantification of organic compounds in complex environmental samples using high-resolution electrospray ionization mass spectrometry

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

Nguyen, Tran B.; Nizkorodov, Sergey; Laskin, Alexander

2013-01-07

Quantitative analysis of individual compounds in complex mixtures using high-resolution electrospray ionization mass spectrometry (HR-ESI-MS) is complicated by differences in the ionization efficiencies of analyte molecules in the mixture, resulting in signal suppression during ionization. However, the ability to obtain concentration estimates of compounds in an environmental sample is important for data interpretation and comparison. We introduce an approach for estimating mass concentrations of analytes observed in a multicomponent mixture by HR-ESI-MS, without prior separation. The approach relies on a calibration of the instrument using appropriate standards added to the mixture of studied analytes. An illustration of how the proposedmore » calibration can be applied in practice is provided for aqueous extracts of isoprene photooxidation organic aerosol, with multifunctional organic acids standards. We show that the observed ion sensitivities in ESI-MS are positively correlated with the “adjusted mass,” defined as a product of the molecular mass and the H/C ratio in the molecule (adjusted mass = H/C x molecular mass). The correlation of the observed ESI sensitivity with adjusted mass is justified by considering trends of the physical and chemical properties of organic compounds that affect ionization in the positive ion mode, i.e., gas-phase basicity, polarizability, and molecular size.« less

Leaching characteristics of toxic constituents from coal fly ash mixed soils under the influence of pH

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

Komonweeraket, Kanokwan; Cetin, Bora, E-mail: bora.cetin@sdsmt.edu; Benson, Craig H., E-mail: chbenson@wisc.edu

Highlights: • The impact of pH on the leaching of elements and metals from fly ash mixed soils. • Generally Ca, Cd, Mg, and Sr follows a cationic leaching pattern. • The leaching of As and Se shows an oxyanionic leaching pattern. • The leaching behavior of elements does not change based on material type. • Different fly ash types show different abilities in immobilizing trace elements. - Abstract: Leaching behaviors of Arsenic (As), Barium (Ba), Calcium (Ca), Cadmium (Cd), Magnesium (Mg), Selenium (Se), and Strontium (Sr) from soil alone, coal fly ash alone, and soil-coal fly ash mixtures, weremore » studied at a pH range of 2–14 via pH-dependent leaching tests. Seven different types of soils and coal fly ashes were tested. Results of this study indicated that Ca, Cd, Mg, and Sr showed cationic leaching pattern while As and Se generally follows an oxyanionic leaching pattern. On the other hand, leaching of Ba presented amphoteric-like leaching pattern but less pH-dependent. In spite of different types and composition of soil and coal fly ash investigated, the study reveals the similarity in leaching behavior as a function of pH for a given element from soil, coal fly ash, and soil-coal fly ash mixtures. The similarity is most likely due to similar controlling mechanisms (e.g., solubility, sorption, and solid-solution formation) and similar controlling factors (e.g., leachate pH and redox conditions). This offers the opportunity to transfer knowledge of coal fly ash that has been extensively characterized and studied to soil stabilized with coal fly ash. It is speculated that unburned carbon in off-specification coal fly ashes may provide sorption sites for Cd resulting in a reduction in concentration of these elements in leachate from soil-coal fly ash mixture. Class C fly ash provides sufficient CaO to initiate the pozzolanic reaction yielding hydrated cement products that oxyanions, including As and Se, can be incorporated into.« less

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

PubMed Central

Feenstra, Bjarke; Skovgaard, Ib M

2004-01-01

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented. PMID:15238544

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

PubMed

Feenstra, Bjarke; Skovgaard, Ib M

2004-06-01

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.

MAPPING SUNKEN POLLUTANT POOLS WITH DEPTH FINDERS

EPA Science Inventory

Many hazardous substances and mixtures are immiscible with and more dense than water. When spillages or releases into waterbodies occur, the hazardous materials will disperse in a pattern controlled by physical properties of the material, flow and dispersion effects, and topograp...

Tremie Concrete for Bridge Piers and Other Massive Underwater Placements

DOT National Transportation Integrated Search

1981-09-01

This study reviewed the placement of mass concrete under water using a tremie. Areas investigated included (a) Mixture design of tremie concrete including the use of pozzolanic replacement of portions of the cement; (b) Flow patterns and flow related...

Effects of dietary mixture of garlic (Allium sativum), coriander (Coriandrum sativum) and probiotics on immune responses and caecal counts in young laying hens.

PubMed

Lee, J S; Kim, M J; Park, S H; Lee, S B; Wang, T; Jung, U S; Im, J; Kim, E J; Lee, K W; Lee, H G

2017-10-01

This study was conducted to evaluate the effects of a combined mixture of phytogenic extracts (garlic and coriander) and probiotics on growth performance and immune responses in laying hens based on the results of in vitro studies to screen for immunomodulatory potency of each ingredient. Several parameters of immunomodulatory potency were estimated using lamina propria leucocytes (LPLs) isolated from rat intestinal mucosa tissue. Results show that the combined mixture enhanced LPLs proliferation, increased LPL-mediated cytotoxicity against YAC-1 tumour cells, and decreased lipopolysaccharide (LPS)-induced cytokine production including tumour necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) in LPLs. For in vivo study, laying hens (n = 50/each diet group) were fed with control diet, a diet containing antibiotics (0.01% per kg feed) or the combined mixture (0.02% per kg feed) for 21 days. The dietary combined mixture improved egg production (p < 0.05) but not growth performance and carcass traits. Interestingly, the patterns of suppressing plasma IFN-γ productions during inflammation by LPS injection and decreasing caecal E. coli counts in the combined mixture group were comparable to those in the antibiotics group. Taken together, our results suggested that the 0.02% of combined mixture of phytogenic extracts and probiotics as ingredients has potential immunomodulatory effects in laying hens. Journal of Animal Physiology and Animal Nutrition © 2016 Blackwell Verlag GmbH.

A retrospective database analysis of insulin use patterns in insulin-naïve patients with type 2 diabetes initiating basal insulin or mixtures

PubMed Central

Bonafede, Machaon MK; Kalsekar, Anupama; Pawaskar, Manjiri; Ruiz, Kimberly M; Torres, Amelito M; Kelly, Karen R; Curkendall, Suellen M

2010-01-01

Objective: To describe insulin persistence among patients with type 2 diabetes initiating insulin therapy with basal insulin or insulin mixtures and determine factors associated with nonpersistence. Research design and methods: The Thomson Reuters MarketScan® databases were used to retrospectively analyze insulin-naïve patients with type 2 diabetes by initiating insulin therapy. Insulin use was described using a variety of measures. The persistence to insulin was described using both a gap-based measure and the number of claims measure. Results: Patients in the basal insulin cohort (N = 15,255) primarily used insulin analogs (88.1%) and vial and syringe (97%). Patients in the mixture cohort (N = 2,732) were more likely to initiate on human insulin mixtures (62.5%) and vial and syringe (68.1%). Average time between insulin refills was 80 and 71 days for basal and mixture initiators, respectively. Nearly, 75% of basal insulin initiators and 65% of insulin mixture initiators had a 90-day gap in insulin prescriptions. More than half of all the patients had at least one insulin prescription per quarter. Patients initiating with insulin analogs were more likely to be persistent compared with those initiating with human insulin across both cohorts and measures of persistence (P < 0.001). Conclusion: Persistence to insulin therapy is poorer than one would anticipate, but appears to be higher in users of insulin analogs and insulin mixtures. PMID:20622915

Inhomogeneous atomic Bose-Fermi mixtures in cubic lattices.

PubMed

Cramer, M; Eisert, J; Illuminati, F

2004-11-05

We determine the ground state properties of inhomogeneous mixtures of bosons and fermions in cubic lattices and parabolic confining potentials. For finite hopping we determine the domain boundaries between Mott-insulator plateaux and hopping-dominated regions for lattices of arbitrary dimension within mean-field and perturbation theory. The results are compared with a new numerical method that is based on a Gutzwiller variational approach for the bosons and an exact treatment for the fermions. The findings can be applied as a guideline for future experiments with trapped atomic Bose-Fermi mixtures in optical lattices.

Environmental Risk Assessment of Pharmaceutical Mixtures: Demands, Gaps, and Possible Bridges.

PubMed

Backhaus, Thomas

2016-07-01

The ecotoxicological risk of pharmaceutical mixtures typically exceeds the risk of each individual compound, which calls specific attention to the fact that monitoring surveys routinely find complex pharmaceutical mixtures in various environmental compartments. However, although the body of evidence on the ecotoxicology of pharmaceutical mixtures is quite consistent, the current guidelines for the environmental risk assessment of pharmaceuticals often do not explicitly address mixture effects. Data availability and acceptable methods often limit such assessments. A tiered approach that begins with summing up individual risk quotients, i.e., the ratio between the predicted or measured environmental concentration and the predicted no effect concentration (PNEC) is therefore suggested in this paper, in order to improve the realism of the environmental risk assessment of pharmaceuticals. Additionally, the use of a mixture-specific assessment factor, as well as the classical mixture toxicity concepts of concentration addition and independent action is explored. Finally, specific attention is given to the exposure-based waiving of environmental risk assessments, as currently implemented in screening or pre-screening phases (tier 0 in Europe, categorical exclusion in the USA), since even low, individually non-toxic concentrations might combine to produce substantial mixture effects.

An analysis of lethal and sublethal interactions among type I and type II pyrethroid pesticide mixtures using standard Hyalella azteca water column toxicity tests.

PubMed

Hoffmann, Krista Callinan; Deanovic, Linda; Werner, Inge; Stillway, Marie; Fong, Stephanie; Teh, Swee

2016-10-01

A novel 2-tiered analytical approach was used to characterize and quantify interactions between type I and type II pyrethroids in Hyalella azteca using standardized water column toxicity tests. Bifenthrin, permethrin, cyfluthrin, and lambda-cyhalothrin were tested in all possible binary combinations across 6 experiments. All mixtures were analyzed for 4-d lethality, and 2 of the 6 mixtures (permethrin-bifenthrin and permethrin-cyfluthrin) were tested for subchronic 10-d lethality and sublethal effects on swimming motility and growth. Mixtures were initially analyzed for interactions using regression analyses, and subsequently compared with the additive models of concentration addition and independent action to further characterize mixture responses. Negative interactions (antagonistic) were significant in 2 of the 6 mixtures tested, including cyfluthrin-bifenthrin and cyfluthrin-permethrin, but only on the acute 4-d lethality endpoint. In both cases mixture responses fell between the additive models of concentration addition and independent action. All other mixtures were additive across 4-d lethality, and bifenthrin-permethrin and cyfluthrin-permethrin were also additive in terms of subchronic 10-d lethality and sublethal responses. Environ Toxicol Chem 2016;35:2542-2549. © 2016 SETAC. © 2016 SETAC.

Evaluation of the nephrotoxicity of complex mixtures containing organics and metals: advantages and disadvantages of the use of real-world complex mixtures.

PubMed

Simmons, J E; Yang, R S; Berman, E

1995-02-01

As part of a multidisciplinary health effects study, the nephrotoxicity of complex industrial waste mixtures was assessed. Adult, male Fischer 344 rats were gavaged with samples of complex industrial waste and nephrotoxicity evaluated 24 hr later. Of the 10 tested samples, 4 produced increased absolute or relative kidney weight, or both, coupled with a statistically significant alteration in at least one of the measured serum parameters (urea nitrogen (BUN), creatinine (CREAT), and BUN/CREAT ratio). Although the waste samples had been analyzed for a number of organic chemicals and 7 of the 10 samples were analyzed also for 12 elemental metals and metalloids, their nephrotoxicity was not readily predicted from the partial chemical characterization data. Because the chemical form or speciation of the metals was unknown, it was not possible to estimate their contribution to the observed biological response. Various experimental approaches, including use of real-world complex mixtures, chemically defined synthetic mixtures, and simple mixtures, will be necessary to adequately determine the potential human health risk from exposure to complex chemical mixtures.

Bench experiments comparing simulated inspiratory effort when breathing helium-oxygen mixtures to that during positive pressure support with air.

PubMed

Martin, Andrew R; Katz, Ira M; Jenöfi, Katharina; Caillibotte, Georges; Brochard, Laurent; Texereau, Joëlle

2012-10-03

Inhalation of helium-oxygen (He/O2) mixtures has been explored as a means to lower the work of breathing of patients with obstructive lung disease. Non-invasive ventilation (NIV) with positive pressure support is also used for this purpose. The bench experiments presented herein were conducted in order to compare simulated patient inspiratory effort breathing He/O2 with that breathing medical air, with or without pressure support, across a range of adult, obstructive disease patterns. Patient breathing was simulated using a dual-chamber mechanical test lung, with the breathing compartment connected to an ICU ventilator operated in NIV mode with medical air or He/O2 (78/22 or 65/35%). Parabolic or linear resistances were inserted at the inlet to the breathing chamber. Breathing chamber compliance was also varied. The inspiratory effort was assessed for the different gas mixtures, for three breathing patterns, with zero pressure support (simulating unassisted spontaneous breathing), and with varying levels of pressure support. Inspiratory effort increased with increasing resistance and decreasing compliance. At a fixed resistance and compliance, inspiratory effort increased with increasing minute ventilation, and decreased with increasing pressure support. For parabolic resistors, inspiratory effort was lower for He/O2 mixtures than for air, whereas little difference was measured for nominally linear resistance. Relatively small differences in inspiratory effort were measured between the two He/O2 mixtures. Used in combination, reductions in inspiratory effort provided by He/O2 and pressure support were additive. The reduction in inspiratory effort afforded by breathing He/O2 is strongly dependent on the severity and type of airway obstruction. Varying helium concentration between 78% and 65% has small impact on inspiratory effort, while combining He/O2 with pressure support provides an additive reduction in inspiratory effort. In addition, breathing He/O2 alone may provide an alternative to pressure support in circumstances where NIV is not available or poorly tolerated.

Modeling of non-thermal plasma in flammable gas mixtures

NASA Astrophysics Data System (ADS)

Napartovich, A. P.; Kochetov, I. V.; Leonov, S. B.

2008-07-01

An idea of using plasma-assisted methods of fuel ignition is based on non-equilibrium generation of chemically active species that speed up the combustion process. It is believed that gain in energy consumed for combustion acceleration by plasmas is due to the non-equilibrium nature of discharge plasma, which allows radicals to be produced in an above-equilibrium amount. Evidently, the size of the effect is strongly dependent on the initial temperature, pressure, and composition of the mixture. Of particular interest is comparison between thermal ignition of a fuel-air mixture and non-thermal plasma initiation of the combustion. Mechanisms of thermal ignition in various fuel-air mixtures have been studied for years, and a number of different mechanisms are known providing an agreement with experiments at various conditions. The problem is -- how to conform thermal chemistry approach to essentially non-equilibrium plasma description. The electric discharge produces much above-equilibrium amounts of chemically active species: atoms, radicals and ions. The point is that despite excess concentrations of a number of species, total concentration of these species is far below concentrations of the initial gas mixture. Therefore, rate coefficients for reactions of these discharge produced species with other gas mixture components are well known quantities controlled by the translational temperature, which can be calculated from the energy balance equation taking into account numerous processes initiated by plasma. A numerical model was developed combining traditional approach of thermal combustion chemistry with advanced description of the plasma kinetics based on solution of electron Boltzmann equation. This approach allows us to describe self-consistently strongly non-equilibrium electric discharge in chemically unstable (ignited) gas. Equations of pseudo-one-dimensional gas dynamics were solved in parallel with a system of thermal chemistry equations, kinetic equations for charged particles (electrons, positive and negative ions), and with the electric circuit equation. The electric circuit comprises power supply, ballast resistor connected in series with the discharge and capacity. Rate coefficients for electron-assisted reactions were calculated from solving the two-term spherical harmonic expansion of the Boltzmann equation. Such an approach allows us to describe influence of thermal chemistry reactions (burning) on the discharge characteristics. Results of comparison between the discharge and thermal ignition effects for mixtures of hydrogen or ethylene with dry air will be reported. Effects of acceleration of ignition by discharge plasma will be analyzed. In particular, the role of singlet oxygen produced effectively in the discharge in ignition speeding up will be discussed.

Genome-Wide Transcription Profiles Reveal Genotype-Dependent Responses of Biological Pathways and Gene-Families in Daphnia Exposed to Single and Mixed Stressors

PubMed Central

2015-01-01

The present study investigated the possibilities and limitations of implementing a genome-wide transcription-based approach that takes into account genetic and environmental variation to better understand the response of natural populations to stressors. When exposing two different Daphnia pulex genotypes (a cadmium-sensitive and a cadmium-tolerant one) to cadmium, the toxic cyanobacteria Microcystis aeruginosa, and their mixture, we found that observations at the transcriptomic level do not always explain observations at a higher level (growth, reproduction). For example, although cadmium elicited an adverse effect at the organismal level, almost no genes were differentially expressed after cadmium exposure. In addition, we identified oxidative stress and polyunsaturated fatty acid metabolism-related pathways, as well as trypsin and neurexin IV gene-families as candidates for the underlying causes of genotypic differences in tolerance to Microcystis. Furthermore, the whole-genome transcriptomic data of a stressor mixture allowed a better understanding of mixture responses by evaluating interactions between two stressors at the gene-expression level against the independent action baseline model. This approach has indicated that ubiquinone pathway and the MAPK serine-threonine protein kinase and collagens gene-families were enriched with genes showing an interactive effect in expression response to exposure to the mixture of the stressors, while transcription and translation-related pathways and gene-families were mostly related with genotypic differences in interactive responses to this mixture. Collectively, our results indicate that the methods we employed may improve further characterization of the possibilities and limitations of transcriptomics approaches in the adverse outcome pathway framework and in predictions of multistressor effects on natural populations. PMID:24552364

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

76 FR 52954 - Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting Adverse...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-24

... observers based on available space. DATES: The workshop will be held September 26-27, 2011, and begin each... prioritize the knowledge gaps and challenges in mixtures research specific to each of the following... close sooner if the 85 spaces for observers are filled. At that time, persons wishing to attend the...

SEPARATION OF VAPOR-PHASE ALCOHOL/WATER MIXTURES VIA FRACTIONAL CONDENSATION USING A PILOT-SCALE DEPHLEGMATOR: ENHANCEMENT OF THE PREVAPORATION PROCESS SEPARATION FACTOR

EPA Science Inventory

In prevaporation, a liquid mixture contacts a membrane surface that preferentially permeates one of the liquid components as a vapor. Our approach to improving pervaporation performance is to replace the one-stage condenser traditionally used to condense the permeate with a frac...

CUMMULATIVE EFFECTS OF ADMINISTRATION MIXTURES OF “ANTIANDROGENS” IN RATS: A NEW FRAMEWORK BASED UPON COMMON SYSTEMS RATHER THAN COMMON MECHANISMS

EPA Science Inventory

Since humans and wildlife are exposed to more than one chemical at a time, concern has arisen about the effects of complex mixtures on reproduction and development. To date, different regulatory groups have not yet developed consistent approaches to conducting assessments of the ...

Dynamical Approach to Multiequilibria Problems for Mixtures of Acids and Their Conjugated Bases

ERIC Educational Resources Information Center

Glaser, Rainer E.; Delarosa, Marco A.; Salau, Ahmed Olasunkanmi; Chicone, Carmen

2014-01-01

Mathematical methods are described for the determination of steady-state concentrations of all species in multiequilibria systems consisting of several acids and their conjugated bases in aqueous solutions. The main example consists of a mixture of a diprotic acid H[subscript 2]A, a monoprotic acid HB, and their conjugate bases. The reaction…

Environmental Barcoding: A Next-Generation Sequencing Approach for Biomonitoring Applications Using River Benthos

PubMed Central

Hajibabaei, Mehrdad; Shokralla, Shadi; Zhou, Xin; Singer, Gregory A. C.; Baird, Donald J.

2011-01-01

Timely and accurate biodiversity analysis poses an ongoing challenge for the success of biomonitoring programs. Morphology-based identification of bioindicator taxa is time consuming, and rarely supports species-level resolution especially for immature life stages. Much work has been done in the past decade to develop alternative approaches for biodiversity analysis using DNA sequence-based approaches such as molecular phylogenetics and DNA barcoding. On-going assembly of DNA barcode reference libraries will provide the basis for a DNA-based identification system. The use of recently introduced next-generation sequencing (NGS) approaches in biodiversity science has the potential to further extend the application of DNA information for routine biomonitoring applications to an unprecedented scale. Here we demonstrate the feasibility of using 454 massively parallel pyrosequencing for species-level analysis of freshwater benthic macroinvertebrate taxa commonly used for biomonitoring. We designed our experiments in order to directly compare morphology-based, Sanger sequencing DNA barcoding, and next-generation environmental barcoding approaches. Our results show the ability of 454 pyrosequencing of mini-barcodes to accurately identify all species with more than 1% abundance in the pooled mixture. Although the approach failed to identify 6 rare species in the mixture, the presence of sequences from 9 species that were not represented by individuals in the mixture provides evidence that DNA based analysis may yet provide a valuable approach in finding rare species in bulk environmental samples. We further demonstrate the application of the environmental barcoding approach by comparing benthic macroinvertebrates from an urban region to those obtained from a conservation area. Although considerable effort will be required to robustly optimize NGS tools to identify species from bulk environmental samples, our results indicate the potential of an environmental barcoding approach for biomonitoring programs. PMID:21533287

Nutritional ecology of entomophagy in humans and other primates.

PubMed

Raubenheimer, David; Rothman, Jessica M

2013-01-01

Entomophagy is widespread among nonhuman primates and is common among many human communities. However, the extent and patterns of entomophagy vary substantially both in humans and nonhuman primates. Here we synthesize the literature to examine why humans and other primates eat insects and what accounts for the variation in the extent to which they do so. Variation in the availability of insects is clearly important, but less understood is the role of nutrients in entomophagy. We apply a multidimensional analytical approach, the right-angled mixture triangle, to published data on the macronutrient compositions of insects to address this. Results showed that insects eaten by humans spanned a wide range of protein-to-fat ratios but were generally nutrient dense, whereas insects with high protein-to-fat ratios were eaten by nonhuman primates. Although suggestive, our survey exposes a need for additional, standardized, data.

WNN 92; Proceedings of the 3rd Workshop on Neural Networks: Academic/Industrial/NASA/Defense, Auburn Univ., AL, Feb. 10-12, 1992 and South Shore Harbour, TX, Nov. 4-6, 1992

NASA Technical Reports Server (NTRS)

Padgett, Mary L. (Editor)

1993-01-01

The present conference discusses such neural networks (NN) related topics as their current development status, NN architectures, NN learning rules, NN optimization methods, NN temporal models, NN control methods, NN pattern recognition systems and applications, biological and biomedical applications of NNs, VLSI design techniques for NNs, NN systems simulation, fuzzy logic, and genetic algorithms. Attention is given to missileborne integrated NNs, adaptive-mixture NNs, implementable learning rules, an NN simulator for travelling salesman problem solutions, similarity-based forecasting, NN control of hypersonic aircraft takeoff, NN control of the Space Shuttle Arm, an adaptive NN robot manipulator controller, a synthetic approach to digital filtering, NNs for speech analysis, adaptive spline networks, an anticipatory fuzzy logic controller, and encoding operations for fuzzy associative memories.

Viscous fingering with partially miscible fluids

NASA Astrophysics Data System (ADS)

Fu, Xiaojing; Cueto-Felgueroso, Luis; Juanes, Ruben

2017-10-01

Viscous fingering—the fluid-mechanical instability that takes place when a low-viscosity fluid displaces a high-viscosity fluid—has traditionally been studied under either fully miscible or fully immiscible fluid systems. Here we study the impact of partial miscibility (a common occurrence in practice) on the fingering dynamics. Through a careful design of the thermodynamic free energy of a binary mixture, we develop a phase-field model of fluid-fluid displacements in a Hele-Shaw cell for the general case in which the two fluids have limited (but nonzero) solubility into one another. We show, by means of high-resolution numerical simulations, that partial miscibility exerts a powerful control on the degree of fingering: fluid dissolution hinders fingering while fluid exsolution enhances fingering. We also show that, as a result of the interplay between compositional exchange and the hydrodynamic pattern-forming process, stronger fingering promotes the system to approach thermodynamic equilibrium more quickly.

Analysis of Glycosaminoglycans Using Mass Spectrometry

PubMed Central

Staples, Gregory O.; Zaia, Joseph

2015-01-01

The glycosaminoglycans (GAGs) are linear polysaccharides expressed on animal cell surfaces and in extracellular matrices. Their biosynthesis is under complex control and confers a domain structure that is essential to their ability to bind to protein partners. Key to understanding the functions of GAGs are methods to determine accurately and rapidly patterns of sulfation, acetylation and uronic acid epimerization that correlate with protein binding or other biological activities. Mass spectrometry (MS) is particularly suitable for the analysis of GAGs for biomedical purposes. Using modern ionization techniques it is possible to accurately determine molecular weights of GAG oligosaccharides and their distributions within a mixture. Methods for direct interfacing with liquid chromatography have been developed to permit online mass spectrometric analysis of GAGs. New tandem mass spectrometric methods for fine structure determination of GAGs are emerging. This review summarizes MS-based approaches for analysis of GAGs, including tissue extraction and chromatographic methods compatible with LC/MS and tandem MS. PMID:25705143

Estimating statistical power for open-enrollment group treatment trials.

PubMed

Morgan-Lopez, Antonio A; Saavedra, Lissette M; Hien, Denise A; Fals-Stewart, William

2011-01-01

Modeling turnover in group membership has been identified as a key barrier contributing to a disconnect between the manner in which behavioral treatment is conducted (open-enrollment groups) and the designs of substance abuse treatment trials (closed-enrollment groups, individual therapy). Latent class pattern mixture models (LCPMMs) are emerging tools for modeling data from open-enrollment groups with membership turnover in recently proposed treatment trials. The current article illustrates an approach to conducting power analyses for open-enrollment designs based on the Monte Carlo simulation of LCPMM models using parameters derived from published data from a randomized controlled trial comparing Seeking Safety to a Community Care condition for women presenting with comorbid posttraumatic stress disorder and substance use disorders. The example addresses discrepancies between the analysis framework assumed in power analyses of many recently proposed open-enrollment trials and the proposed use of LCPMM for data analysis. Copyright © 2011 Elsevier Inc. All rights reserved.

Are polychlorinated biphenyl residues adequately describe by aroclor mixture equivalents. Isomer-specific principal components analysis of such residues in fish and turtles

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

Schwartz, T.R.; Stalling, D.L.; Rice, C.L.

1987-01-01

Polychlorinated biphenyl (PCB) residues from fish and turtles were analyzed with SIMCA (Soft Independent Modeling of Class Analogy), a principal components analysis technique. A series of technical Aroclors were also analyzed to provide a reference data set for pattern recognition. Environmental PCB residues are often expressed in terms of relative Aroclor composition. In this work, we assessed the similarity of Aroclors to class models derived for fish and turtles to ascertain if the PCB residues in the samples could be described by an Aroclor or Aroclor mixture. Using PCA, we found that these samples could not be described by anmore » Aroclor or Aroclor mixture and that it would be inappropriate to report these samples as such. 18 references, 3 figures, 3 tables.« less

Near-limit flame structures at low Lewis number

NASA Technical Reports Server (NTRS)

Ronney, Paul D.

1990-01-01

The characteristics of premixed gas flames in mixtures with low Lewis numbers near flammability limits were studied experimentally using a low-gravity environment to reduce buoyant convection. The behavior of such flames was found to be dominated by diffusive-thermal instabilities. For sufficiently reactive mixtures, cellular structures resulting from these instabilities were observed and found to spawn new cells in regular patterns. For less reactive mixtures, cells formed shortly after ignition but did not spawn new cells; instead these cells evolved into a flame structure composed of stationary, apparently stable spherical flamelets. Experimental observations are found to be in qualitative agreement with elementary analytical models based on the interaction of heat release due to chemical reaction, differential diffusion of thermal energy and mass, flame front curvature, and volumetric heat losses due to gas and/or soot radiation.

A study of the propagation, dynamics, and extinguishment of cellular flames using microgravity techniques

NASA Technical Reports Server (NTRS)

Ronney, Paul D.

1989-01-01

The characteristics of premixed gas flames in mixtures with low Lewis numbers, free of natural convection effects, were investigated and found to be dominated by diffusive-thermal instabilities. For sufficiently reactive mixtures, cellular structures resulting from these instabilities were observed and found to spawn new cells in regular patterns. For less reactive mixtures, cells formed shortly after ignition but did not spawn new cells; instead these cells evolved into a flame structure composed of stationary, apparently stable spherical flamelets. As a result of these phenomena, well-defined flammability limits were not observed. The experimental results are found to be in qualitative agreement with a simple analytical model based on the interaction of heat release due to chemical reaction, differential diffusion of thermal energy and mass, flame front curvature, and heat losses due to gas radiation.

Medicines, shaken and stirred: a critical review on the ecotoxicology of pharmaceutical mixtures

PubMed Central

Backhaus, Thomas

2014-01-01

Analytical monitoring surveys routinely confirm that organisms in the environment are exposed to complex multi-component pharmaceutical mixtures. We are hence tasked with the challenge to take this into consideration when investigating the ecotoxicology of pharmaceuticals. This review first provides a brief overview of the fundamental approaches for mixture toxicity assessment, which is then followed by a critical review on the empirical evidence that is currently at hand on the ecotoxicology of pharmaceutical mixtures. It is concluded that, while the classical concepts of concentration addition and independent action (response addition) provide a robust scientific footing, several knowledge gaps remain. This includes, in particular, the need for more and better empirical data on the effects of pharmaceutical mixtures on soil organisms as well as marine flora and fauna, and exploring the quantitative consequences of toxicokinetic, toxicodynamic and ecological interactions. Increased focus should be put on investigating the ecotoxicology of pharmaceutical mixtures in environmentally realistic settings. PMID:25405972

Analyzing Dyadic Sequence Data—Research Questions and Implied Statistical Models

PubMed Central

Fuchs, Peter; Nussbeck, Fridtjof W.; Meuwly, Nathalie; Bodenmann, Guy

2017-01-01

The analysis of observational data is often seen as a key approach to understanding dynamics in romantic relationships but also in dyadic systems in general. Statistical models for the analysis of dyadic observational data are not commonly known or applied. In this contribution, selected approaches to dyadic sequence data will be presented with a focus on models that can be applied when sample sizes are of medium size (N = 100 couples or less). Each of the statistical models is motivated by an underlying potential research question, the most important model results are presented and linked to the research question. The following research questions and models are compared with respect to their applicability using a hands on approach: (I) Is there an association between a particular behavior by one and the reaction by the other partner? (Pearson Correlation); (II) Does the behavior of one member trigger an immediate reaction by the other? (aggregated logit models; multi-level approach; basic Markov model); (III) Is there an underlying dyadic process, which might account for the observed behavior? (hidden Markov model); and (IV) Are there latent groups of dyads, which might account for observing different reaction patterns? (mixture Markov; optimal matching). Finally, recommendations for researchers to choose among the different models, issues of data handling, and advises to apply the statistical models in empirical research properly are given (e.g., in a new r-package “DySeq”). PMID:28443037

Alternative Approaches to Assessing Nonresponse Bias in Longitudinal Survey Estimates: An Application to Substance-Use Outcomes Among Young Adults in the United States

PubMed Central

West, Brady Thomas; McCabe, Sean Esteban

2017-01-01

Abstract We evaluated alternative approaches to assessing and correcting for nonresponse bias in a longitudinal survey. We considered the changes in substance-use outcomes over a 3-year period among young adults aged 18–24 years (n = 5,199) in the United States, analyzing data from the National Epidemiologic Survey on Alcohol and Related Conditions. This survey collected a variety of substance-use information from a nationally representative sample of US adults in 2 waves: 2001–2002 and 2004–2005. We first considered nonresponse rates in the second wave as a function of key substance-use outcomes in wave 1. We then evaluated 5 alternative approaches designed to correct for nonresponse bias under different attrition mechanisms, including weighting adjustments, multiple imputation, selection models, and pattern-mixture models. Nonignorable attrition in a longitudinal survey can lead to bias in estimates of change in certain health behaviors over time, and only selected procedures enable analysts to assess the sensitivity of their inferences to different assumptions about the extent of nonignorability. We compared estimates based on these 5 approaches, and we suggest a road map for assessing the risk of nonresponse bias in longitudinal studies. We conclude with directions for future research in this area given the results of our evaluations. PMID:28338839

Multibeam sonar (DIDSON) assessment of American shad (Alosa sapidissima) approaching a hydroelectric dam

USGS Publications Warehouse

Grote, Ann B.; Bailey, Michael M.; Zydlewski, Joseph D.; Hightower, Joseph E.

2014-01-01

We investigated the fish community approaching the Veazie Dam on the Penobscot River, Maine, prior to implementation of a major dam removal and river restoration project. Multibeam sonar (dual-frequency identification sonar, DIDSON) surveys were conducted continuously at the fishway entrance from May to July in 2011. A 5% subsample of DIDSON data contained 43 793 fish targets, the majority of which were of Excellent (15.7%) or Good (73.01%) observation quality. Excellent quality DIDSON targets (n = 6876) were apportioned by species using a Bayesian mixture model based on four known fork length distributions (river herring (alewife,Alosa psuedoharengus, and blueback herring, Alosa aestivalis), American shad, Alosa sapidissima) and two size classes (one sea-winter and multi-sea-winter) of Atlantic salmon (Salmo salar). 76.2% of targets were assigned to the American shad distribution; Atlantic salmon accounted for 15.64%, and river herring 8.16% of observed targets. Shad-sized (99.0%) and salmon-sized (99.3%) targets approached the fishway almost exclusively during the day, whereas river herring-sized targets were observed both during the day (51.1%) and at night (48.9%). This approach demonstrates how multibeam sonar imaging can be used to evaluate community composition and species-specific movement patterns in systems where there is little overlap in the length distributions of target species.

Predicting phase behavior of mixtures of reservoir fluids with carbon dioxide

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

Grigg, R.B.; Lingane, P.J.

1983-01-01

The use of an equation of state to predict phase behavior during carbon dioxide flooding is well established. The characterization of the C/sub 7/ fraction and the selection of interaction parameters are the most important variables. Single-contact phase behavior is presented for mixtures of Ford Geraldine (Delaware), Maljamar (Grayburg), West Sussex (Shannon), and Reservoir D reservoir fluids, and of a synthetic oil with carbon dioxide. The phase behavior of these mixtures can be reproduced using 3 to 5 pseudo components and common interaction parameters. The critical properties of the pseudo components are calculated from detailed oil characterizations. Because the parametersmore » are not further adjusted, this approach reduces the empiricism in fitting phase data and may result in a more accurate representation of the system as the composition of the oil changes during the approach to miscibility. 21 references.« less

A Generalized Mixture Framework for Multi-label Classification

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

We develop a novel probabilistic ensemble framework for multi-label classification that is based on the mixtures-of-experts architecture. In this framework, we combine multi-label classification models in the classifier chains family that decompose the class posterior distribution P(Y1, …, Yd|X) using a product of posterior distributions over components of the output space. Our approach captures different input–output and output–output relations that tend to change across data. As a result, we can recover a rich set of dependency relations among inputs and outputs that a single multi-label classification model cannot capture due to its modeling simplifications. We develop and present algorithms for learning the mixtures-of-experts models from data and for performing multi-label predictions on unseen data instances. Experiments on multiple benchmark datasets demonstrate that our approach achieves highly competitive results and outperforms the existing state-of-the-art multi-label classification methods. PMID:26613069

Short-term bioassay of complex organic mixtures. Part II. Mutagenicity testing

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

Epler, J.L.; Clark, B.R.; Ho, C.

1978-01-01

The feasibility of using short-term mutagenicity assays to predict the potential biohazard of various crude and complex test materials has been examined in a coupled chemical and biological approach. The principal focus of the research has involved the preliminary chemical characterizatiion and preparation for bioassay, followed by testing in the Salmonella histidine reversion assay system. The mutagenicity tests are intended to act as predictors of profound long-range health effects such as mutagenesis and/or carcinogenesis; act as a mechanism to rapidly isolate and identify a hazardous agent in a complex mixture; and function as a measure of biological activity correlating baselinemore » data with changes in process conditions. Since complex mixtures can be fractionated and approached in these short-term assays, information reflecting on the actual compounds responsible for the biological effect may be accumulated.« less

Mixture theory-based poroelasticity as a model of interstitial tissue growth

PubMed Central

Cowin, Stephen C.; Cardoso, Luis

2011-01-01

This contribution presents an alternative approach to mixture theory-based poroelasticity by transferring some poroelastic concepts developed by Maurice Biot to mixture theory. These concepts are a larger RVE and the subRVE-RVE velocity average tensor, which Biot called the micro-macro velocity average tensor. This velocity average tensor is assumed here to depend upon the pore structure fabric. The formulation of mixture theory presented is directed toward the modeling of interstitial growth, that is to say changing mass and changing density of an organism. Traditional mixture theory considers constituents to be open systems, but the entire mixture is a closed system. In this development the mixture is also considered to be an open system as an alternative method of modeling growth. Growth is slow and accelerations are neglected in the applications. The velocity of a solid constituent is employed as the main reference velocity in preference to the mean velocity concept from the original formulation of mixture theory. The standard development of statements of the conservation principles and entropy inequality employed in mixture theory are modified to account for these kinematic changes and to allow for supplies of mass, momentum and energy to each constituent and to the mixture as a whole. The objective is to establish a basis for the development of constitutive equations for growth of tissues. PMID:22184481

Mixture theory-based poroelasticity as a model of interstitial tissue growth.

PubMed

Cowin, Stephen C; Cardoso, Luis

2012-01-01

This contribution presents an alternative approach to mixture theory-based poroelasticity by transferring some poroelastic concepts developed by Maurice Biot to mixture theory. These concepts are a larger RVE and the subRVE-RVE velocity average tensor, which Biot called the micro-macro velocity average tensor. This velocity average tensor is assumed here to depend upon the pore structure fabric. The formulation of mixture theory presented is directed toward the modeling of interstitial growth, that is to say changing mass and changing density of an organism. Traditional mixture theory considers constituents to be open systems, but the entire mixture is a closed system. In this development the mixture is also considered to be an open system as an alternative method of modeling growth. Growth is slow and accelerations are neglected in the applications. The velocity of a solid constituent is employed as the main reference velocity in preference to the mean velocity concept from the original formulation of mixture theory. The standard development of statements of the conservation principles and entropy inequality employed in mixture theory are modified to account for these kinematic changes and to allow for supplies of mass, momentum and energy to each constituent and to the mixture as a whole. The objective is to establish a basis for the development of constitutive equations for growth of tissues.

3D/3D registration of coronary CTA and biplane XA reconstructions for improved image guidance

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

Dibildox, Gerardo, E-mail: g.dibildox@erasmusmc.nl; Baka, Nora; Walsum, Theo van

2014-09-15

Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions. Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment ismore » achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available. Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P > 0.1) but did improve robustness with regards to the initialization of the 3D models. Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.« less

Mixtures Research at NIEHS: An Evolving Program

PubMed Central

Rider, Cynthia V; Carlin, Danielle J; DeVito, Micheal J; Thompson, Claudia L; Walker, Nigel J

2014-01-01

The National Institute of Environmental Health Sciences (NIEHS) has a rich history in evaluating the toxicity of mixtures. The types of mixtures assessed by the Division of the National Toxicology Program (DNTP) and the extramural community (through the Division of Extramural Research and Training (DERT)) have included a broad range of chemicals and toxicants, with each study having a unique set of questions and design considerations. Some examples of the types of mixtures studied include: groundwater contaminants, pesticides/fertilizers, dioxin-like chemicals (assessing the toxic equivalency approach), drug combinations, air pollution, metals, polycyclic aromatic hydrocarbons, technical mixtures (e.g. pentachlorophenol, flame retardants), and mixed entities (e.g. herbals, asbestos). These endeavors have provided excellent data on the toxicity of specific mixtures and have been informative to the human health risk assessment process in general (e.g. providing data on low dose exposures to environmental chemicals). However, the mixtures research effort at NIEHS, to date, has been driven by test article nominations to the DNTP or by investigator-initiated research through DERT. Recently, the NIEHS has embarked upon an effort to coordinate mixtures research across both intramural and extramural divisions in order to maximize mixtures research results. A path forward for NIEHS mixtures research will be based on feedback from a Request for Information (RFI) designed to gather up-to-date views on the knowledge gaps and roadblocks to evaluating mixtures and performing cumulative risk assessment, and a workshop organized to bring together mixtures experts from risk assessment, exposure science, biology, epidemiology, and statistics. The future of mixtures research at NIEHS will include projects from nominations to DNTP, studies by extramural investigators, and collaborations across government agencies that address high-priority questions in the field of mixtures research. PMID:23146757

Cumulative toxicity of neonicotinoid insecticide mixtures to Chironomus dilutus under acute exposure scenarios.

PubMed

Maloney, Erin M; Morrissey, Christy A; Headley, John V; Peru, Kerry M; Liber, Karsten

2017-11-01

Extensive agricultural use of neonicotinoid insecticide products has resulted in the presence of neonicotinoid mixtures in surface waters worldwide. Although many aquatic insect species are known to be sensitive to neonicotinoids, the impact of neonicotinoid mixtures is poorly understood. In the present study, the cumulative toxicities of binary and ternary mixtures of select neonicotinoids (imidacloprid, clothianidin, and thiamethoxam) were characterized under acute (96-h) exposure scenarios using the larval midge Chironomus dilutus as a representative aquatic insect species. Using the MIXTOX approach, predictive parametric models were fitted and statistically compared with observed toxicity in subsequent mixture tests. Single-compound toxicity tests yielded median lethal concentration (LC50) values of 4.63, 5.93, and 55.34 μg/L for imidacloprid, clothianidin, and thiamethoxam, respectively. Because of the similar modes of action of neonicotinoids, concentration-additive cumulative mixture toxicity was the predicted model. However, we found that imidacloprid-clothianidin mixtures demonstrated response-additive dose-level-dependent synergism, clothianidin-thiamethoxam mixtures demonstrated concentration-additive synergism, and imidacloprid-thiamethoxam mixtures demonstrated response-additive dose-ratio-dependent synergism, with toxicity shifting from antagonism to synergism as the relative concentration of thiamethoxam increased. Imidacloprid-clothianidin-thiamethoxam ternary mixtures demonstrated response-additive synergism. These results indicate that, under acute exposure scenarios, the toxicity of neonicotinoid mixtures to C. dilutus cannot be predicted using the common assumption of additive joint activity. Indeed, the overarching trend of synergistic deviation emphasizes the need for further research into the ecotoxicological effects of neonicotinoid insecticide mixtures in field settings, the development of better toxicity models for neonicotinoid mixture exposures, and the consideration of mixture effects when setting water quality guidelines for this class of pesticides. Environ Toxicol Chem 2017;36:3091-3101. © 2017 SETAC. © 2017 SETAC.

Chemical mixtures in untreated water from public-supply wells in the U.S. — Occurrence, composition, and potential toxicity

USGS Publications Warehouse

Toccalino, Patricia L.; Norman, Julia E.; Scott, Jonathon C.

2012-01-01

Chemical mixtures are prevalent in groundwater used for public water supply, but little is known about their potential health effects. As part of a large-scale ambient groundwater study, we evaluated chemical mixtures across multiple chemical classes, and included more chemical contaminants than in previous studies of mixtures in public-supply wells. We (1) assessed the occurrence of chemical mixtures in untreated source-water samples from public-supply wells, (2) determined the composition of the most frequently occurring mixtures, and (3) characterized the potential toxicity of mixtures using a new screening approach. The U.S. Geological Survey collected one untreated water sample from each of 383 public wells distributed across 35 states, and analyzed the samples for as many as 91 chemical contaminants. Concentrations of mixture components were compared to individual human-health benchmarks; the potential toxicity of mixtures was characterized by addition of benchmark-normalized component concentrations. Most samples (84%) contained mixtures of two or more contaminants, each at concentrations greater than one-tenth of individual benchmarks. The chemical mixtures that most frequently occurred and had the greatest potential toxicity primarily were composed of trace elements (including arsenic, strontium, or uranium), radon, or nitrate. Herbicides, disinfection by-products, and solvents were the most common organic contaminants in mixtures. The sum of benchmark-normalized concentrations was greater than 1 for 58% of samples, suggesting that there could be potential for mixtures toxicity in more than half of the public-well samples. Our findings can be used to help set priorities for groundwater monitoring and suggest future research directions for drinking-water treatment studies and for toxicity assessments of chemical mixtures in water resources.

Widely Tunable Morphologies in Block Copolymer Thin Films Through Solvent Vapor Annealing Using Mixtures of Selective Solvents

PubMed Central

Chavis, Michelle A.; Smilgies, Detlef-M.; Wiesner, Ulrich B.; Ober, Christopher K.

2015-01-01

Thin films of block copolymers are extremely attractive for nanofabrication because of their ability to form uniform and periodic nanoscale structures by microphase separation. One shortcoming of this approach is that to date the design of a desired equilibrium structure requires synthesis of a block copolymer de novo within the corresponding volume ratio of the blocks. In this work, we investigated solvent vapor annealing in supported thin films of poly(2-hydroxyethyl methacrylate)-block-poly(methyl methacrylate) [PHEMA-b-PMMA] by means of grazing incidence small angle X–ray scattering (GISAXS). A spin-coated thin film of lamellar block copolymer was solvent vapor annealed to induce microphase separation and improve the long-range order of the self-assembled pattern. Annealing in a mixture of solvent vapors using a controlled volume ratio of solvents (methanol, MeOH, and tetrahydrofuran, THF), which are chosen to be preferential for each block, enabled selective formation of ordered lamellae, gyroid, hexagonal or spherical morphologies from a single block copolymer with a fixed volume fraction. The selected microstructure was then kinetically trapped in the dry film by rapid drying. To our knowledge, this paper describes the first reported case where in-situ methods are used to study the transition of block copolymer films from one initial disordered morphology to four different ordered morphologies, covering much of the theoretical diblock copolymer phase diagram. PMID:26819574

Development of a food spoilage indicator for monitoring freshness of skinless chicken breast.

PubMed

Rukchon, Chompoonoot; Nopwinyuwong, Atchareeya; Trevanich, Sudsai; Jinkarn, Tunyarut; Suppakul, Panuwat

2014-12-01

A colorimetric mixed-pH dye-based indicator with potential for the development of intelligent packaging, as a "chemical barcode" for real-time monitoring of skinless chicken breast spoilage, is described. Also investigated was the relationship between the numbers of microorganisms and the amount of volatile compounds. This on-package indicator contains two groups of pH-sensitive dyes, one of which is a mixture of bromothymol blue and methyl red, while the other is a mixture of bromothymol blue, bromocresol green and phenol red. Carbon dioxide (CO2) was used as a spoilage metabolite because the degree of spoilage was related to the amount of increased CO2, and which was more than the level of total volatile basic nitrogen (TVB-N) during the storage period. Characteristics of the two groups of indicator solutions were studied, as well as their response to CO2. A kinetic approach was used to correlate the response of the indicator label to the changes in skinless chicken breast spoilage. Color changes, in terms of total color difference of a mixed-pH dye-based indicator, correlated well with CO2 levels of skinless chicken breast. Trials on skinless chicken breast samples have verified that the indicator response correlates with microbial growth patterns, thus enabling real-time monitoring of spoilage either at various constant temperatures or with temperature fluctuation. Copyright © 2014 Elsevier B.V. All rights reserved.

DNA-polyfluorophore Chemosensors for Environmental Remediation: Vapor-phase Identification of Petroleum Products in Contaminated Soil†

PubMed Central

Jiang, Wei; Wang, Shenliang; Yuen, Lik Hang; Kwon, Hyukin; Ono, Toshikazu

2013-01-01

Contamination of soil and groundwater by petroleum-based products is an extremely widespread and important environmental problem. Here we have tested a simple optical approach for detecting and identifying such industrial contaminants in soil samples, using a set of fluorescent DNA-based chemosensors in pattern-based sensing. We used a set of diverse industrial volatile chemicals to screen and identify a set of five short oligomeric DNA fluorophores on PEG-polystyrene microbeads that could differentiate the entire set after exposure to their vapors in air. We then tested this set of five fluorescent chemosensor compounds for their ability to respond with fluorescence changes when exposed to headgas over soil samples contaminated with one of ten different samples of crude oil, petroleum distillates, fuels, lubricants and additives. Statistical analysis of the quantitative fluorescence change data (as Δ(R,G,B) emission intensities) revealed that these five chemosensors on beads could differentiate all ten product mixtures at 1000 ppm in soil within 30 minutes. Tests of sensitivity with three of the contaminant mixtures showed that they could be detected and differentiated in amounts at least as low as one part per million in soil. The results establish that DNA-polyfluorophores may have practical utility in monitoring the extent and identity of environmental spills and leaks, while they occur and during their remediation. PMID:23878719

Application of Project Portfolio Management

NASA Astrophysics Data System (ADS)

Pankowska, Malgorzata

The main goal of the chapter is the presentation of the application project portfolio management approach to support development of e-Municipality and public administration information systems. The models of how people publish and utilize information on the web have been transformed continually. Instead of simply viewing on static web pages, users publish their own content through blogs and photo- and video-sharing slides. Analysed in this chapter, ICT (Information Communication Technology) projects for municipalities cover the mixture of the static web pages, e-Government information systems, and Wikis. So, for the management of the ICT projects' mixtures the portfolio project management approach is proposed.

Kurtosis Approach for Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.

Synthesis of the zeolitic imidazolate framework ZIF-4 from the ionic liquid 1-butyl-3-methylimidazolium imidazolate

NASA Astrophysics Data System (ADS)

Hovestadt, Maximilian; Schwegler, Johannes; Schulz, Peter S.; Hartmann, Martin

2018-05-01

A new synthesis route for the zeolitic imidazolate framework ZIF-4 using imidazolium imidazolate is reported. Additionally, the ionic liquid-derived material is compared to conventional ZIF-4 with respect to the powder X-ray diffraction pattern pattern, nitrogen uptake, particle size, and separation potential for olefin/paraffin gas mixtures. Higher synthesis yields were obtained, and the different particle size affected the performance in the separation of ethane and ethylene.

Trajectories of premorbid childhood and adolescent functioning in schizophrenia-spectrum psychoses: A first-episode study.

PubMed

Horton, Leslie E; Tarbox, Sarah I; Olino, Thomas M; Haas, Gretchen L

2015-06-30

Evidence of social and behavioral problems preceding the onset of schizophrenia-spectrum psychoses is consistent with a neurodevelopmental model of these disorders. Here we predict that individuals with a first episode of schizophrenia-spectrum psychoses will evidence one of three patterns of premorbid adjustment: an early deficit, a deteriorating pattern, or adequate or good social adjustment. Participants were 164 (38% female; 31% black) individuals ages 15-50 with a first episode of schizophrenia-spectrum psychoses. Premorbid adjustment was assessed using the Cannon-Spoor Premorbid Adjustment Scale. We compared the fit of a series of growth mixture models to examine premorbid adjustment trajectories, and found the following 3-class model provided the best fit with: a "stable-poor" adjustment class (54%), a "stable-good" adjustment class (39%), and a "deteriorating" adjustment class (7%). Relative to the "stable-good" class, the "stable-poor" class experienced worse negative symptoms at 1-year follow-up, particularly in the social amotivation domain. This represents the first known growth mixture modeling study to examine premorbid functioning patterns in first-episode schizophrenia-spectrum psychoses. Given that the stable-poor adjustment pattern was most prevalent, detection of social and academic maladjustment as early as childhood may help identify people at increased risk for schizophrenia-spectrum psychoses, potentially increasing feasibility of early interventions. Published by Elsevier Ireland Ltd.

Laser imaging in liquid-liquid flows

NASA Astrophysics Data System (ADS)

Abidin, M. I. I. Zainal; Park, Kyeong H.; Voulgaropoulos, Victor; Chinaud, Maxime; Angeli, Panagiota

2016-11-01

In this work, the flow patterns formed during the horizontal flow of two immiscible liquids are studied. The pipe is made from acrylic, has an ID of 26 mm and a length of 4 m. A silicone oil (5cSt) and a water/glycerol mixture are used as test fluids. This set of liquids is chosen to match the refractive indices of the phases and enable laser based flow pattern identification. A double pulsed Nd:Yag laser was employed (532mm) with the appropriate optics to generate a laser sheet at the middle of the pipe. The aqueous phase was dyed with Rhodamine 6G, to distinguish between the two phases. Experiments were carried out for mixture velocities ranging from 0.15 to 2 m/s. Different inlet designs were used to actuate flow patterns in a controlled way and observe their development downstream the test section. A static mixer produced dispersed flow at the inlet which separated downstream due to enhanced coalescence. On the other hand, the use of a cylindrical bluff body at the inlet created non-linear interfacial waves in initially stratified flows from which drops detached leading to the transition to dispersed patterns. From the detailed images important flow parameters were measured such as wave characteristics and drop size. Project funded under the UK Engineering and Physical Sciences Research Council (EPSRC) Programme Grant MEMPHIS.

Engineering Escherichia coli coculture systems for the production of biochemical products.

PubMed

Zhang, Haoran; Pereira, Brian; Li, Zhengjun; Stephanopoulos, Gregory

2015-07-07

Engineering microbial consortia to express complex biosynthetic pathways efficiently for the production of valuable compounds is a promising approach for metabolic engineering and synthetic biology. Here, we report the design, optimization, and scale-up of an Escherichia coli-E. coli coculture that successfully overcomes fundamental microbial production limitations, such as high-level intermediate secretion and low-efficiency sugar mixture utilization. For the production of the important chemical cis,cis-muconic acid, we show that the coculture approach achieves a production yield of 0.35 g/g from a glucose/xylose mixture, which is significantly higher than reported in previous reports. By efficiently producing another compound, 4-hydroxybenzoic acid, we also demonstrate that the approach is generally applicable for biosynthesis of other important industrial products.

ANALYSIS OF GLYCANS DERIVED FROM GLYCOCONJUGATES BY CAPILLARY ELECTROPHORESIS-MASS SPECTROMETRY

PubMed Central

Mechref, Yehia

2012-01-01

The high structural variation of glycan derived from glycoconjugates, which substantially increases with the molecular size of a protein, contributes to the complexity of glycosylation patterns commonly associated with glycoconjugates. In the case of glycoproteins, such variation originates from the multiple glycosylation sites of proteins and the number of glycan structures associated with each site (microheterogeneity). The ability to comprehensively characterize highly complex mixture of glycans has been analytically stimulating and challenging. Although the most powerful mass spectrometric (MS) and tandem MS techniques are capable of providing a wealth of structural information, they are still not able to readily identify isomeric glycan structures without high order tandem MS (MSn). The analysis of isomeric glycan structures has been attained using several separation methods, including high-pH anion exchange chromatography (HPAEC), hydrophilic interaction chromatography (HILIC) and gas chromatography (GC). However, capillary electrophoresis (CE) and microfluidics capillary electrophoresis (MCE) offer high separation efficiency and resolutions, allowing the separation of closely related glycan structures. Therefore, interfacing CE and MCE to MS is a powerful analytical approach, allowing potentially comprehensive and sensitive analysis of complex glycan samples. This review describes and discusses the utility of different CE and MCE approaches in the structural characterization of glycoproteins and the feasibility of interfacing these approaches to mass spectrometry. PMID:22180203

Embryotoxic and teratogenic effects of petroleum hydrocarbons in mallards (Anas platyrhynchos)

USGS Publications Warehouse

Hoffman, D.J.

1979-01-01

Egg surface applications of microliter quantities of crude and refined oils of high aromatic content are embryotoxic to mallards (Anas platyrhynchos) and other avian species; applications of aliphatic hydrocarbons have virtually no effect. Mallard eggs at 72 h of development were exposed to a mixture of aromatic hydrocarbons or to aromatic compounds representative to those present in crude oil to assess their toxicity. The class composition of the mixture was similar to that of South Louisiana crude oil, an American Petroleum Institute reference oil. Application of 20 microliter of the mixture reduced embryonic survival by nearly 70%. The temporal pattern of embryonic death was similar to that after exposure to South Louisiana crude oil. Embryonic growth was stunted, as reflected by weight, crown-rump length, and bill length, and there was a significant increase in the incidence of abnormal survivors. When individual classes of aromatic hydrocarbons were tested, tetracyclics caused some embryonic death at the concentrations in the mixture. When classes were tested in all possible combinations of two, no combination appeared to be as toxic as the entire mixture. Addition of the tetracyclic compound chrysene to the aromatic mixture considerably enhanced embryotoxicity, but could not completely account for the toxicity of the crude oil. The presence of additional unidentified polycyclic aromatic hydrocarbons as well as methylated derivatives of polycyclic aromatic compounds such as chrysene may further account for the embryotoxicity of the crude oil.

Effect of an acute intraluminal administration of capsaicin on oesophageal motor pattern in GORD patients with ineffective oesophageal motility.

PubMed

Grossi, L; Cappello, G; Marzio, L

2006-08-01

Ineffective oesophageal motility (IOM) is a functional disorder affecting about 50% of gastro-oesophageal reflux disease (GORD) patients. This disease in a severe form limits the clearing ability of the oesophagus and is considered one of the predictive factors for poorer GORD resolution. Capsaicin, the active compound of red pepper, exerts a prokinetic effect on oesophageal motility in healthy subjects by increasing the amplitude of body waves, even if no evidence exists on its possible role in situations of reduced motility. The aim of the study was to evaluate the effect of an acute administration of capsaicin on the oesophageal motor pattern in a group of GORD patients affected by severe IOM. Twelve GORD patients with severe IOM received an intra-oesophageal administration of 2 mL of a red pepper-olive oil mixture and 2 mL of olive oil alone serving as a control during a stationary manometry. The motor patterns of the oesophageal body and lower oesophageal sphincter (LOS) were analysed at baseline and after the infusion of the two stimuli. The administration of capsaicin induced a significant improvement in oesophageal body contractility when compared with baseline. The velocity of propagation of waves and the LOS basal tone remained unchanged. The motor pattern was unaltered by the administration of olive oil alone. An acute administration of capsaicin seems to improve the motor performance of the oesophageal body in patients with ineffective motility. Whether this could represent the basis for further therapeutic approaches of GORD patients needs further study.