Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality.

PubMed

Yang, Lei; Qin, Guoyou; Zhao, Naiqing; Wang, Chunfang; Song, Guixiang

2012-10-30

Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton's method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality

PubMed Central

2012-01-01

Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Methods Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton’s method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. Results In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. Conclusions GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies. PMID:23110601

Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

PubMed Central

Bouvet, J-M; Makouanzi, G; Cros, D; Vigneron, Ph

2016-01-01

Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information. PMID:26328760

Validation analysis of probabilistic models of dietary exposure to food additives.

PubMed

Gilsenan, M B; Thompson, R L; Lambe, J; Gibney, M J

2003-10-01

The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

This study statistically analyzed a grain-size based additivity model that has been proposed to scale reaction rates and parameters from laboratory to field. The additivity model assumed that reaction properties in a sediment including surface area, reactive site concentration, reaction rate, and extent can be predicted from field-scale grain size distribution by linearly adding reaction properties for individual grain size fractions. This study focused on the statistical analysis of the additivity model with respect to reaction rate constants using multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment as an example. Experimental data of rate-limited U(VI) desorption in amore » stirred flow-cell reactor were used to estimate the statistical properties of multi-rate parameters for individual grain size fractions. The statistical properties of the rate constants for the individual grain size fractions were then used to analyze the statistical properties of the additivity model to predict rate-limited U(VI) desorption in the composite sediment, and to evaluate the relative importance of individual grain size fractions to the overall U(VI) desorption. The result indicated that the additivity model provided a good prediction of the U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model, and U(VI) desorption in individual grain size fractions have to be simulated in order to apply the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel size fraction (2-8mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

A regularized variable selection procedure in additive hazards model with stratified case-cohort design.

PubMed

Ni, Ai; Cai, Jianwen

2018-07-01

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.

PubMed

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2013-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data

PubMed Central

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2012-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions. PMID:23645976

Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.

PubMed

Bonnafous, Fanny; Fievet, Ghislain; Blanchet, Nicolas; Boniface, Marie-Claude; Carrère, Sébastien; Gouzy, Jérôme; Legrand, Ludovic; Marage, Gwenola; Bret-Mestries, Emmanuelle; Munos, Stéphane; Pouilly, Nicolas; Vincourt, Patrick; Langlade, Nicolas; Mangin, Brigitte

2018-02-01

This study compares five models of GWAS, to show the added value of non-additive modeling of allelic effects to identify genomic regions controlling flowering time of sunflower hybrids. Genome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

Implementing Generalized Additive Models to Estimate the Expected Value of Sample Information in a Microsimulation Model: Results of Three Case Studies.

PubMed

Rabideau, Dustin J; Pei, Pamela P; Walensky, Rochelle P; Zheng, Amy; Parker, Robert A

2018-02-01

The expected value of sample information (EVSI) can help prioritize research but its application is hampered by computational infeasibility, especially for complex models. We investigated an approach by Strong and colleagues to estimate EVSI by applying generalized additive models (GAM) to results generated from a probabilistic sensitivity analysis (PSA). For 3 potential HIV prevention and treatment strategies, we estimated life expectancy and lifetime costs using the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model, a complex patient-level microsimulation model of HIV progression. We fitted a GAM-a flexible regression model that estimates the functional form as part of the model fitting process-to the incremental net monetary benefits obtained from the CEPAC PSA. For each case study, we calculated the expected value of partial perfect information (EVPPI) using both the conventional nested Monte Carlo approach and the GAM approach. EVSI was calculated using the GAM approach. For all 3 case studies, the GAM approach consistently gave similar estimates of EVPPI compared with the conventional approach. The EVSI behaved as expected: it increased and converged to EVPPI for larger sample sizes. For each case study, generating the PSA results for the GAM approach required 3 to 4 days on a shared cluster, after which EVPPI and EVSI across a range of sample sizes were evaluated in minutes. The conventional approach required approximately 5 weeks for the EVPPI calculation alone. Estimating EVSI using the GAM approach with results from a PSA dramatically reduced the time required to conduct a computationally intense project, which would otherwise have been impractical. Using the GAM approach, we can efficiently provide policy makers with EVSI estimates, even for complex patient-level microsimulation models.

Research on Capacity Addition using Market Model with Transmission Congestion under Competitive Environment

NASA Astrophysics Data System (ADS)

Katsura, Yasufumi; Attaviriyanupap, Pathom; Kataoka, Yoshihiko

In this research, the fundamental premises for deregulation of the electric power industry are reevaluated. The authors develop a simple model to represent wholesale electricity market with highly congested network. The model is developed by simplifying the power system and market in New York ISO based on available data of New York ISO in 2004 with some estimation. Based on the developed model and construction cost data from the past, the economic impact of transmission line addition on market participants and the impact of deregulation on power plant additions under market with transmission congestion are studied. Simulation results show that the market signals may fail to facilitate proper capacity additions and results in the undesirable over-construction and insufficient-construction cycle of capacity addition.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when

Effects of additional food in a delayed predator-prey model.

PubMed

Sahoo, Banshidhar; Poria, Swarup

2015-03-01

We examine the effects of supplying additional food to predator in a gestation delay induced predator-prey system with habitat complexity. Additional food works in favor of predator growth in our model. Presence of additional food reduces the predatory attack rate to prey in the model. Supplying additional food we can control predator population. Taking time delay as bifurcation parameter the stability of the coexisting equilibrium point is analyzed. Hopf bifurcation analysis is done with respect to time delay in presence of additional food. The direction of Hopf bifurcations and the stability of bifurcated periodic solutions are determined by applying the normal form theory and the center manifold theorem. The qualitative dynamical behavior of the model is simulated using experimental parameter values. It is observed that fluctuations of the population size can be controlled either by supplying additional food suitably or by increasing the degree of habitat complexity. It is pointed out that Hopf bifurcation occurs in the system when the delay crosses some critical value. This critical value of delay strongly depends on quality and quantity of supplied additional food. Therefore, the variation of predator population significantly effects the dynamics of the model. Model results are compared with experimental results and biological implications of the analytical findings are discussed in the conclusion section. Copyright © 2015 Elsevier Inc. All rights reserved.

Generalized linear and generalized additive models in studies of species distributions: Setting the scene

USGS Publications Warehouse

Guisan, Antoine; Edwards, T.C.; Hastie, T.

2002-01-01

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001. We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling. ?? 2002 Elsevier Science B.V. All rights reserved.

Comprehensive European dietary exposure model (CEDEM) for food additives.

PubMed

Tennant, David R

2016-05-01

European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database.

Flood loss model transfer: on the value of additional data

NASA Astrophysics Data System (ADS)

Schröter, Kai; Lüdtke, Stefan; Vogel, Kristin; Kreibich, Heidi; Thieken, Annegret; Merz, Bruno

2017-04-01

The transfer of models across geographical regions and flood events is a key challenge in flood loss estimation. Variations in local characteristics and continuous system changes require regional adjustments and continuous updating with current evidence. However, acquiring data on damage influencing factors is expensive and therefore assessing the value of additional data in terms of model reliability and performance improvement is of high relevance. The present study utilizes empirical flood loss data on direct damage to residential buildings available from computer aided telephone interviews that were carried out after the floods in 2002, 2005, 2006, 2010, 2011 and 2013 mainly in the Elbe and Danube catchments in Germany. Flood loss model performance is assessed for incrementally increased numbers of loss data which are differentiated according to region and flood event. Two flood loss modeling approaches are considered: (i) a multi-variable flood loss model approach using Random Forests and (ii) a uni-variable stage damage function. Both model approaches are embedded in a bootstrapping process which allows evaluating the uncertainty of model predictions. Predictive performance of both models is evaluated with regard to mean bias, mean absolute and mean squared errors, as well as hit rate and sharpness. Mean bias and mean absolute error give information about the accuracy of model predictions; mean squared error and sharpness about precision and hit rate is an indicator for model reliability. The results of incremental, regional and temporal updating demonstrate the usefulness of additional data to improve model predictive performance and increase model reliability, particularly in a spatial-temporal transfer setting.

Fine-mapping additive and dominant SNP effects using group-LASSO and Fractional Resample Model Averaging

PubMed Central

Sabourin, Jeremy; Nobel, Andrew B.; Valdar, William

2014-01-01

Genomewide association studies sometimes identify loci at which both the number and identities of the underlying causal variants are ambiguous. In such cases, statistical methods that model effects of multiple SNPs simultaneously can help disentangle the observed patterns of association and provide information about how those SNPs could be prioritized for follow-up studies. Current multi-SNP methods, however, tend to assume that SNP effects are well captured by additive genetics; yet when genetic dominance is present, this assumption translates to reduced power and faulty prioritizations. We describe a statistical procedure for prioritizing SNPs at GWAS loci that efficiently models both additive and dominance effects. Our method, LLARRMA-dawg, combines a group LASSO procedure for sparse modeling of multiple SNP effects with a resampling procedure based on fractional observation weights; it estimates for each SNP the robustness of association with the phenotype both to sampling variation and to competing explanations from other SNPs. In producing a SNP prioritization that best identifies underlying true signals, we show that: our method easily outperforms a single marker analysis; when additive-only signals are present, our joint model for additive and dominance is equivalent to or only slightly less powerful than modeling additive-only effects; and, when dominance signals are present, even in combination with substantial additive effects, our joint model is unequivocally more powerful than a model assuming additivity. We also describe how performance can be improved through calibrated randomized penalization, and discuss how dominance in ungenotyped SNPs can be incorporated through either heterozygote dosage or multiple imputation. PMID:25417853

SEMIPARAMETRIC ADDITIVE RISKS REGRESSION FOR TWO-STAGE DESIGN SURVIVAL STUDIES

PubMed Central

Li, Gang; Wu, Tong Tong

2011-01-01

In this article we study a semiparametric additive risks model (McKeague and Sasieni (1994)) for two-stage design survival data where accurate information is available only on second stage subjects, a subset of the first stage study. We derive two-stage estimators by combining data from both stages. Large sample inferences are developed. As a by-product, we also obtain asymptotic properties of the single stage estimators of McKeague and Sasieni (1994) when the semiparametric additive risks model is misspecified. The proposed two-stage estimators are shown to be asymptotically more efficient than the second stage estimators. They also demonstrate smaller bias and variance for finite samples. The developed methods are illustrated using small intestine cancer data from the SEER (Surveillance, Epidemiology, and End Results) Program. PMID:21931467

Formation and reduction of carcinogenic furan in various model systems containing food additives.

PubMed

Kim, Jin-Sil; Her, Jae-Young; Lee, Kwang-Geun

2015-12-15

The aim of this study was to analyse and reduce furan in various model systems. Furan model systems consisting of monosaccharides (0.5M glucose and ribose), amino acids (0.5M alanine and serine) and/or 1.0M ascorbic acid were heated at 121°C for 25 min. The effects of food additives (each 0.1M) such as metal ions (iron sulphate, magnesium sulphate, zinc sulphate and calcium sulphate), antioxidants (BHT and BHA), and sodium sulphite on the formation of furan were measured. The level of furan formed in the model systems was 6.8-527.3 ng/ml. The level of furan in the model systems of glucose/serine and glucose/alanine increased 7-674% when food additives were added. In contrast, the level of furan decreased by 18-51% in the Maillard reaction model systems that included ribose and alanine/serine with food additives except zinc sulphate. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modelling the behaviour of additives in gun barrels

NASA Astrophysics Data System (ADS)

Rhodes, N.; Ludwig, J. C.

1986-01-01

A mathematical model which predicts the flow and heat transfer in a gun barrel is described. The model is transient, two-dimensional and equations are solved for velocities and enthalpies of a gas phase, which arises from the combustion of propellant and cartridge case, for particle additives which are released from the case; volume fractions of the gas and particles. Closure of the equations is obtained using a two-equation turbulence model. Preliminary calculations are described in which the proportions of particle additives in the cartridge case was altered. The model gives a good prediction of the ballistic performance and the gas to wall heat transfer. However, the expected magnitude of reduction in heat transfer when particles are present is not predicted. The predictions of gas flow invalidate some of the assumptions made regarding case and propellant behavior during combustion and further work is required to investigate these effects and other possible interactions, both chemical and physical, between gas and particles.

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

The additivity model assumed that field-scale reaction properties in a sediment including surface area, reactive site concentration, and reaction rate can be predicted from field-scale grain-size distribution by linearly adding reaction properties estimated in laboratory for individual grain-size fractions. This study evaluated the additivity model in scaling mass transfer-limited, multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment. Experimental data of rate-limited U(VI) desorption in a stirred flow-cell reactor were used to estimate the statistical properties of the rate constants for individual grain-size fractions, which were then used to predict rate-limited U(VI) desorption in the composite sediment. The resultmore » indicated that the additivity model with respect to the rate of U(VI) desorption provided a good prediction of U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel-size fraction (2 to 8 mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

Does the model of additive effect in placebo research still hold true? A narrative review

PubMed Central

Berger, Bettina; Weger, Ulrich; Heusser, Peter

2017-01-01

Personalised and contextualised care has been turned into a major demand by people involved in healthcare suggesting to move toward person-centred medicine. The assessment of person-centred medicine can be most effectively achieved if treatments are investigated using ‘with versus without’ person-centredness or integrative study designs. However, this assumes that the components of an integrative or person-centred intervention have an additive relationship to produce the total effect. Beecher’s model of additivity assumes an additive relation between placebo and drug effects and is thus presenting an arithmetic summation. So far, no review has been carried out assessing the validity of the additive model, which is to be questioned and more closely investigated in this review. Initial searches for primary studies were undertaken in July 2016 using Pubmed and Google Scholar. In order to find matching publications of similar magnitude for the comparison part of this review, corresponding matches for all included reviews were sought. A total of 22 reviews and 3 clinical and experimental studies fulfilled the inclusion criteria. The results pointed to the following factors actively questioning the additive model: interactions of various effects, trial design, conditioning, context effects and factors, neurobiological factors, mechanism of action, statistical factors, intervention-specific factors (alcohol, caffeine), side-effects and type of intervention. All but one of the closely assessed publications was questioning the additive model. A closer examination of study design is necessary. An attempt in a more systematic approach geared towards solutions could be a suggestion for future research in this field. PMID:28321318

Does the model of additive effect in placebo research still hold true? A narrative review.

PubMed

Boehm, Katja; Berger, Bettina; Weger, Ulrich; Heusser, Peter

2017-03-01

Personalised and contextualised care has been turned into a major demand by people involved in healthcare suggesting to move toward person-centred medicine. The assessment of person-centred medicine can be most effectively achieved if treatments are investigated using 'with versus without' person-centredness or integrative study designs. However, this assumes that the components of an integrative or person-centred intervention have an additive relationship to produce the total effect. Beecher's model of additivity assumes an additive relation between placebo and drug effects and is thus presenting an arithmetic summation. So far, no review has been carried out assessing the validity of the additive model, which is to be questioned and more closely investigated in this review. Initial searches for primary studies were undertaken in July 2016 using Pubmed and Google Scholar. In order to find matching publications of similar magnitude for the comparison part of this review, corresponding matches for all included reviews were sought. A total of 22 reviews and 3 clinical and experimental studies fulfilled the inclusion criteria. The results pointed to the following factors actively questioning the additive model: interactions of various effects, trial design, conditioning, context effects and factors, neurobiological factors, mechanism of action, statistical factors, intervention-specific factors (alcohol, caffeine), side-effects and type of intervention. All but one of the closely assessed publications was questioning the additive model. A closer examination of study design is necessary. An attempt in a more systematic approach geared towards solutions could be a suggestion for future research in this field.

An electrical circuit model for additive-modified SnO2 ceramics

NASA Astrophysics Data System (ADS)

Karami Horastani, Zahra; Alaei, Reza; Karami, Amirhossein

2018-05-01

In this paper an electrical circuit model for additive-modified metal oxide ceramics based on their physical structures and electrical resistivities is presented. The model predicts resistance of the sample at different additive concentrations and different temperatures. To evaluate the model two types of composite ceramics, SWCNT/SnO2 with SWCNT concentrations of 0.3, 0.6, 1.2, 2.4 and 3.8%wt, and Ag/SnO2 with Ag concentrations of 0.3, 0.5, 0.8 and 1.5%wt, were prepared and their electrical resistances versus temperature were experimentally measured. It is shown that the experimental data are in good agreement with the results obtained from the model. The proposed model can be used in the design process of ceramic-based gas sensors, and it also clarifies the role of additive in gas sensing process of additive-modified metal oxide gas sensors. Furthermore the model can be used in the system level modeling of designs in which these sensors are also present.

A Single-Boundary Accumulator Model of Response Times in an Addition Verification Task

PubMed Central

Faulkenberry, Thomas J.

2017-01-01

Current theories of mathematical cognition offer competing accounts of the interplay between encoding and calculation in mental arithmetic. Additive models propose that manipulations of problem format do not interact with the cognitive processes used in calculation. Alternatively, interactive models suppose that format manipulations have a direct effect on calculation processes. In the present study, we tested these competing models by fitting participants' RT distributions in an arithmetic verification task with a single-boundary accumulator model (the shifted Wald distribution). We found that in addition to providing a more complete description of RT distributions, the accumulator model afforded a potentially more sensitive test of format effects. Specifically, we found that format affected drift rate, which implies that problem format has a direct impact on calculation processes. These data give further support for an interactive model of mental arithmetic. PMID:28769853

Modeling and experimental studies on intermittent starch feeding and citrate addition in simultaneous saccharification and fermentation of starch to flavor compounds.

PubMed

Chavan, Abhijit R; Raghunathan, Anuradha; Venkatesh, K V

2009-04-01

Simultaneous saccharification and fermentation (SSF) is a combined process of saccharification of a renewable bioresource and fermentation process to produce products, such as lactic acid and ethanol. Recently, SSF has been extensively used to convert various sources of cellulose and starch into fermentative products. Here, we present a study on production of buttery flavors, namely diacetyl and acetoin, by growing Lactobacillus rhamnosus on a starch medium containing the enzyme glucoamylase. We further develop a structured kinetics for the SSF process, which includes enzyme and growth kinetics. The model was used to simulate the effect of pH and temperature on the SSF process so as to obtain optimum operating conditions. The model was experimentally verified by conducting SSF using an initial starch concentration of 100 g/L. The study demonstrated that the developed kinetic was able to suggest strategies for improved productivities. The developed model was able to accurately predict the enhanced productivity of flavors in a three stage process with intermittent addition of starch. Experimental and simulations demonstrated that citrate addition can also lead to enhanced productivity of flavors. The developed optimal model for SSF was able to capture the dynamics of SSF in batch mode as well as in a three stage process. The structured kinetics was also able to quantify the effect of multiple substrates present in the medium. The study demonstrated that structured kinetic models can be used in the future for design and optimization of SSF as a batch or a fed-batch process.

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

NASA Technical Reports Server (NTRS)

Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

2013-01-01

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

[Assessment of the effect of selected mixture of food additives on the protein metabolism--model studies].

PubMed

Friedrich, Mariola; Kuchlewska, Magdalena

2012-01-01

Contemporarily, food production without food additives is very rare. Increasingly often, however, scientific works report on adverse effects of specified, single food additives on the body. Data is, in turn, lacking on the synergistic effect of a mixture of different food additives on body functions and its main metabolic pathways. The objective of this study, an animal model, was to evaluate if and in what way the compound of chosen and most frequently used and consumed food additives, along with the change of diet composition to processed, purified, influence the selected markers of protein metabolism. The animals were divided into four groups, which were fed with compound of feed pellets: group I and II with basic compound, group III and IV with modified compound in which part of the full grain was replaced by isocalorie wheat flour type 500 and saccharose. Animals from groups I and III received tap water, which was standing for some time, to drink. Animals from groups II and IV received solution of chosen additives to food and next they were given water to drink. The amount of given food additives was evaluated by taking into consideration their consumption by people recalculated to 1 kg of their body mass. The experiment spanned for 7 weeks. It was ascertained that the applied additives caused significant changes in total protein concentration and its fractions: albumin, alpha1-globulin, alpha2-globulin, beta-globulin and gamma-globulin in the blood serum of the animals under research, which can indicate and contribute to disclosure of creation of undesirable food reaction, especially when recommended levels of consumption of those additives are being exceeded. The organism response to the applied additives and accompanying it change of diet was essentially connected to sex of the animals. Undesirable character of changes taking place under the influence of applied additives, was observed both in animals fed with basic feed and modified feed with various

Model studies of hydrogen atom addition and abstraction processes involving ortho-, meta-, and para-benzynes.

PubMed

Clark, A E; Davidson, E R

2001-10-31

H-atom addition and abstraction processes involving ortho-, meta-, and para-benzyne have been investigated by multiconfigurational self-consistent field methods. The H(A) + H(B)...H(C) reaction (where r(BC) is adjusted to mimic the appropriate singlet-triplet energy gap) is shown to effectively model H-atom addition to benzyne. The doublet multiconfiguration wave functions are shown to mix the "singlet" and "triplet" valence bond structures of H(B)...H(C) along the reaction coordinate; however, the extent of mixing is dependent on the singlet-triplet energy gap (DeltaE(ST)) of the H(B)...H(C) diradical. Early in the reaction, the ground-state wave function is essentially the "singlet" VB function, yet it gains significant "triplet" VB character along the reaction coordinate that allows H(A)-H(B) bond formation. Conversely, the wave function of the first excited state is predominantly the "triplet" VB configuration early in the reaction coordinate, but gains "singlet" VB character when the H-atom is close to a radical center. As a result, the potential energy surface (PES) for H-atom addition to triplet H(B)...H(C) diradical is repulsive! The H3 model predicts, in agreement with the actual calculations on benzyne, that the singlet diradical electrons are not coupled strongly enough to give rise to an activation barrier associated with C-H bond formation. Moreover, this model predicts that the PES for H-atom addition to triplet benzyne will be characterized by a repulsive curve early in the reaction coordinate, followed by a potential avoided crossing with the (pi)1(sigma*)1 state of the phenyl radical. In contrast to H-atom addition, large activation barriers characterize the abstraction process in both the singlet ground state and first triplet state. In the ground state, this barrier results from the weakly avoided crossing of the dominant VB configurations in the ground-state singlet (S0) and first excited singlet (S1) because of the large energy gap between S0

Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models

NASA Astrophysics Data System (ADS)

Bouskill, N. J.; Riley, W. J.; Tang, J. Y.

2014-12-01

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowground respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model-observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.

Generalised additive modelling approach to the fermentation process of glutamate.

PubMed

Liu, Chun-Bo; Li, Yun; Pan, Feng; Shi, Zhong-Ping

2011-03-01

In this work, generalised additive models (GAMs) were used for the first time to model the fermentation of glutamate (Glu). It was found that three fermentation parameters fermentation time (T), dissolved oxygen (DO) and oxygen uptake rate (OUR) could capture 97% variance of the production of Glu during the fermentation process through a GAM model calibrated using online data from 15 fermentation experiments. This model was applied to investigate the individual and combined effects of T, DO and OUR on the production of Glu. The conditions to optimize the fermentation process were proposed based on the simulation study from this model. Results suggested that the production of Glu can reach a high level by controlling concentration levels of DO and OUR to the proposed optimization conditions during the fermentation process. The GAM approach therefore provides an alternative way to model and optimize the fermentation process of Glu. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models

DOE PAGES

Bouskill, N. J.; Riley, W. J.; Tang, J. Y.

2014-12-11

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowgroundmore » respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model–observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha -1 yr -1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.« less

Comparison of prosthetic models produced by traditional and additive manufacturing methods.

PubMed

Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong; Kim, Woong-Chul

2015-08-01

The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). The mean marginal gaps and internal gaps showed significant differences according to tooth type (P<.001 and P<.001, respectively) and manufacturing method (P<.037 and P<.001, respectively). Micro-SLA did not show any significant difference from CLWT regarding mean marginal gap compared to the WBM and MJM methods. The mean values of gaps resulting from the four different manufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing.

Marginal regression approach for additive hazards models with clustered current status data.

PubMed

Su, Pei-Fang; Chi, Yunchan

2014-01-15

Current status data arise naturally from tumorigenicity experiments, epidemiology studies, biomedicine, econometrics and demographic and sociology studies. Moreover, clustered current status data may occur with animals from the same litter in tumorigenicity experiments or with subjects from the same family in epidemiology studies. Because the only information extracted from current status data is whether the survival times are before or after the monitoring or censoring times, the nonparametric maximum likelihood estimator of survival function converges at a rate of n(1/3) to a complicated limiting distribution. Hence, semiparametric regression models such as the additive hazards model have been extended for independent current status data to derive the test statistics, whose distributions converge at a rate of n(1/2) , for testing the regression parameters. However, a straightforward application of these statistical methods to clustered current status data is not appropriate because intracluster correlation needs to be taken into account. Therefore, this paper proposes two estimating functions for estimating the parameters in the additive hazards model for clustered current status data. The comparative results from simulation studies are presented, and the application of the proposed estimating functions to one real data set is illustrated. Copyright © 2013 John Wiley & Sons, Ltd.

Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

PubMed

Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

2014-04-02

The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

Doubly Robust Additive Hazards Models to Estimate Effects of a Continuous Exposure on Survival.

PubMed

Wang, Yan; Lee, Mihye; Liu, Pengfei; Shi, Liuhua; Yu, Zhi; Abu Awad, Yara; Zanobetti, Antonella; Schwartz, Joel D

2017-11-01

The effect of an exposure on survival can be biased when the regression model is misspecified. Hazard difference is easier to use in risk assessment than hazard ratio and has a clearer interpretation in the assessment of effect modifications. We proposed two doubly robust additive hazards models to estimate the causal hazard difference of a continuous exposure on survival. The first model is an inverse probability-weighted additive hazards regression. The second model is an extension of the doubly robust estimator for binary exposures by categorizing the continuous exposure. We compared these with the marginal structural model and outcome regression with correct and incorrect model specifications using simulations. We applied doubly robust additive hazard models to the estimation of hazard difference of long-term exposure to PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 microns) on survival using a large cohort of 13 million older adults residing in seven states of the Southeastern United States. We showed that the proposed approaches are doubly robust. We found that each 1 μg m increase in annual PM2.5 exposure was associated with a causal hazard difference in mortality of 8.0 × 10 (95% confidence interval 7.4 × 10, 8.7 × 10), which was modified by age, medical history, socioeconomic status, and urbanicity. The overall hazard difference translates to approximately 5.5 (5.1, 6.0) thousand deaths per year in the study population. The proposed approaches improve the robustness of the additive hazards model and produce a novel additive causal estimate of PM2.5 on survival and several additive effect modifications, including social inequality.

Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

NASA Astrophysics Data System (ADS)

Saleh Ahmar, Ansari; Guritno, Suryo; Abdurakhman; Rahman, Abdul; Awi; Alimuddin; Minggi, Ilham; Arif Tiro, M.; Kasim Aidid, M.; Annas, Suwardi; Utami Sutiksno, Dian; Ahmar, Dewi S.; Ahmar, Kurniawan H.; Abqary Ahmar, A.; Zaki, Ahmad; Abdullah, Dahlan; Rahim, Robbi; Nurdiyanto, Heri; Hidayat, Rahmat; Napitupulu, Darmawan; Simarmata, Janner; Kurniasih, Nuning; Andretti Abdillah, Leon; Pranolo, Andri; Haviluddin; Albra, Wahyudin; Arifin, A. Nurani M.

2018-01-01

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression Zt = 0,106+0,204Z t-1+0,401Z t-2-329X 1(t)+115X 2(t)+35,9X 3(t) and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.

Geo-additive modelling of malaria in Burundi

PubMed Central

2011-01-01

Background Malaria is a major public health issue in Burundi in terms of both morbidity and mortality, with around 2.5 million clinical cases and more than 15,000 deaths each year. It is still the single main cause of mortality in pregnant women and children below five years of age. Because of the severe health and economic burden of malaria, there is still a growing need for methods that will help to understand the influencing factors. Several studies/researches have been done on the subject yielding different results as which factors are most responsible for the increase in malaria transmission. This paper considers the modelling of the dependence of malaria cases on spatial determinants and climatic covariates including rainfall, temperature and humidity in Burundi. Methods The analysis carried out in this work exploits real monthly data collected in the area of Burundi over 12 years (1996-2007). Semi-parametric regression models are used. The spatial analysis is based on a geo-additive model using provinces as the geographic units of study. The spatial effect is split into structured (correlated) and unstructured (uncorrelated) components. Inference is fully Bayesian and uses Markov chain Monte Carlo techniques. The effects of the continuous covariates are modelled by cubic p-splines with 20 equidistant knots and second order random walk penalty. For the spatially correlated effect, Markov random field prior is chosen. The spatially uncorrelated effects are assumed to be i.i.d. Gaussian. The effects of climatic covariates and the effects of other spatial determinants are estimated simultaneously in a unified regression framework. Results The results obtained from the proposed model suggest that although malaria incidence in a given month is strongly positively associated with the minimum temperature of the previous months, regional patterns of malaria that are related to factors other than climatic variables have been identified, without being able to explain

Modeling the cardiovascular system using a nonlinear additive autoregressive model with exogenous input

NASA Astrophysics Data System (ADS)

Riedl, M.; Suhrbier, A.; Malberg, H.; Penzel, T.; Bretthauer, G.; Kurths, J.; Wessel, N.

2008-07-01

The parameters of heart rate variability and blood pressure variability have proved to be useful analytical tools in cardiovascular physics and medicine. Model-based analysis of these variabilities additionally leads to new prognostic information about mechanisms behind regulations in the cardiovascular system. In this paper, we analyze the complex interaction between heart rate, systolic blood pressure, and respiration by nonparametric fitted nonlinear additive autoregressive models with external inputs. Therefore, we consider measurements of healthy persons and patients suffering from obstructive sleep apnea syndrome (OSAS), with and without hypertension. It is shown that the proposed nonlinear models are capable of describing short-term fluctuations in heart rate as well as systolic blood pressure significantly better than similar linear ones, which confirms the assumption of nonlinear controlled heart rate and blood pressure. Furthermore, the comparison of the nonlinear and linear approaches reveals that the heart rate and blood pressure variability in healthy subjects is caused by a higher level of noise as well as nonlinearity than in patients suffering from OSAS. The residue analysis points at a further source of heart rate and blood pressure variability in healthy subjects, in addition to heart rate, systolic blood pressure, and respiration. Comparison of the nonlinear models within and among the different groups of subjects suggests the ability to discriminate the cohorts that could lead to a stratification of hypertension risk in OSAS patients.

A case study on topology optimized design for additive manufacturing

NASA Astrophysics Data System (ADS)

Gebisa, A. W.; Lemu, H. G.

2017-12-01

Topology optimization is an optimization method that employs mathematical tools to optimize material distribution in a part to be designed. Earlier developments of topology optimization considered conventional manufacturing techniques that have limitations in producing complex geometries. This has hindered the topology optimization efforts not to fully be realized. With the emergence of additive manufacturing (AM) technologies, the technology that builds a part layer upon a layer directly from three dimensional (3D) model data of the part, however, producing complex shape geometry is no longer an issue. Realization of topology optimization through AM provides full design freedom for the design engineers. The article focuses on topologically optimized design approach for additive manufacturing with a case study on lightweight design of jet engine bracket. The study result shows that topology optimization is a powerful design technique to reduce the weight of a product while maintaining the design requirements if additive manufacturing is considered.

Additions to Mars Global Reference Atmospheric Model (MARS-GRAM)

NASA Technical Reports Server (NTRS)

Justus, C. G.; James, Bonnie

1992-01-01

Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification was also made which allows heights to go 'below' local terrain height and return 'realistic' pressure, density, and temperature, and not the surface values, as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local 'valley' areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch versions of Mars-GRAM are presented.

Additions to Mars Global Reference Atmospheric Model (Mars-GRAM)

NASA Technical Reports Server (NTRS)

Justus, C. G.

1991-01-01

Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification has also been made which allows heights to go below local terrain height and return realistic pressure, density, and temperature (not the surface values) as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local valley areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch version of Mars-GRAM are presented.

Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

NASA Technical Reports Server (NTRS)

Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar

2015-01-01

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition

Rain water transport and storage in a model sandy soil with hydrogel particle additives.

PubMed

Wei, Y; Durian, D J

2014-10-01

We study rain water infiltration and drainage in a dry model sandy soil with superabsorbent hydrogel particle additives by measuring the mass of retained water for non-ponding rainfall using a self-built 3D laboratory set-up. In the pure model sandy soil, the retained water curve measurements indicate that instead of a stable horizontal wetting front that grows downward uniformly, a narrow fingered flow forms under the top layer of water-saturated soil. This rain water channelization phenomenon not only further reduces the available rain water in the plant root zone, but also affects the efficiency of soil additives, such as superabsorbent hydrogel particles. Our studies show that the shape of the retained water curve for a soil packing with hydrogel particle additives strongly depends on the location and the concentration of the hydrogel particles in the model sandy soil. By carefully choosing the particle size and distribution methods, we may use the swollen hydrogel particles to modify the soil pore structure, to clog or extend the water channels in sandy soils, or to build water reservoirs in the plant root zone.

Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PubMed

Baquero, Oswaldo Santos; Santana, Lidia Maria Reis; Chiaravalloti-Neto, Francisco

2018-01-01

Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in turn, timely and efficient interventions to reduce the burden of the disease. We conducted a comparative study of dengue predictions in São Paulo city to test the performance of trained seasonal autoregressive integrated moving average models, generalized additive models and artificial neural networks. We also used a naïve model as a benchmark. A generalized additive model with lags of the number of cases and meteorological variables had the best performance, predicted epidemics of unprecedented magnitude and its performance was 3.16 times higher than the benchmark and 1.47 higher that the next best performing model. The predictive models captured the seasonal patterns but differed in their capacity to anticipate large epidemics and all outperformed the benchmark. In addition to be able to predict epidemics of unprecedented magnitude, the best model had computational advantages, since its training and tuning was straightforward and required seconds or at most few minutes. These are desired characteristics to provide timely results for decision makers. However, it should be noted that predictions are made just one month ahead and this is a limitation that future studies could try to reduce.

A family of triaxial modified Hubble mass models: Effects of the additional radial functions

NASA Astrophysics Data System (ADS)

Das, Mousumi; Thakur, Parijat; Ann, H. B.

2005-03-01

The projected properties of triaxial generalization of the modified Hubble mass models are studied. These models are constructed by adding the additional radial functions, each multiplied by a low-order spherical harmonic, to the models of [Chakraborty, D.K., Thakur, P., 2000. MNRAS 318, 1273]. The projected surface density of mass models can be calculated analytically which allows us to derive the analytic expressions of axial ratio and position angle of major axis of constant density elliptical contours at asymptotic radii. The models are more general than those studied earlier in the sense that the inclusions of additional terms in density distribution, allow one to produce varieties of the radial profile of axial ratio and position angle, in particular, their small scale variations at inner radii. Strong correlations are found to exist between the observed axial ratio evaluated at 0.25Re and at 4Re which occupy well-separated regions in the parameter space for different choices of the intrinsic axial ratios. These correlations can be exploited to predict the intrinsic shape of the mass model, independent of the viewing angles. Using Bayesian statistics, the result of a test case launched for an estimation of the shape of a model galaxy is found to be satisfactory.

3D model of filler melting with micro-beam plasma arc based on additive manufacturing technology

NASA Astrophysics Data System (ADS)

Chen, Weilin; Yang, Tao; Yang, Ruixin

2017-07-01

Additive manufacturing technology is a systematic process based on discrete-accumulation principle, which is derived by the dimension of parts. Aiming at the dimension mathematical model and slicing problems in additive manufacturing process, the constitutive relations between micro-beam plasma welding parameters and the dimension of part were investigated. The slicing algorithm and slicing were also studied based on the dimension characteristics. By using the direct slicing algorithm according to the geometric characteristics of model, a hollow thin-wall spherical part was fabricated by 3D additive manufacturing technology using micro-beam plasma.

Electroacoustics modeling of piezoelectric welders for ultrasonic additive manufacturing processes

NASA Astrophysics Data System (ADS)

Hehr, Adam; Dapino, Marcelo J.

2016-04-01

Ultrasonic additive manufacturing (UAM) is a recent 3D metal printing technology which utilizes ultrasonic vibrations from high power piezoelectric transducers to additively weld similar and dissimilar metal foils. CNC machining is used intermittent of welding to create internal channels, embed temperature sensitive components, sensors, and materials, and for net shaping parts. Structural dynamics of the welder and work piece influence the performance of the welder and part quality. To understand the impact of structural dynamics on UAM, a linear time-invariant model is used to relate system shear force and electric current inputs to the system outputs of welder velocity and voltage. Frequency response measurements are combined with in-situ operating measurements of the welder to identify model parameters and to verify model assumptions. The proposed LTI model can enhance process consistency, performance, and guide the development of improved quality monitoring and control strategies.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

PubMed Central

Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

2012-01-01

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

Modeling process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Yu, Cheng; Liu, Zeliang; Lian, Yanping; Wolff, Sarah; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-02-01

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the processstructure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a highefficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

Additional EIPC Study Analysis. Final Report

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

Hadley, Stanton W; Gotham, Douglas J.; Luciani, Ralph L.

Between 2010 and 2012 the Eastern Interconnection Planning Collaborative (EIPC) conducted a major long-term resource and transmission study of the Eastern Interconnection (EI). With guidance from a Stakeholder Steering Committee (SSC) that included representatives from the Eastern Interconnection States Planning Council (EISPC) among others, the project was conducted in two phases. Phase 1 involved a long-term capacity expansion analysis that involved creation of eight major futures plus 72 sensitivities. Three scenarios were selected for more extensive transmission- focused evaluation in Phase 2. Five power flow analyses, nine production cost model runs (including six sensitivities), and three capital cost estimations weremore » developed during this second phase. The results from Phase 1 and 2 provided a wealth of data that could be examined further to address energy-related questions. A list of 14 topics was developed for further analysis. This paper brings together the earlier interim reports of the first 13 topics plus one additional topic into a single final report.« less

Modeling of Ti-W Solidification Microstructures Under Additive Manufacturing Conditions

NASA Astrophysics Data System (ADS)

Rolchigo, Matthew R.; Mendoza, Michael Y.; Samimi, Peyman; Brice, David A.; Martin, Brian; Collins, Peter C.; LeSar, Richard

2017-07-01

Additive manufacturing (AM) processes have many benefits for the fabrication of alloy parts, including the potential for greater microstructural control and targeted properties than traditional metallurgy processes. To accelerate utilization of this process to produce such parts, an effective computational modeling approach to identify the relationships between material and process parameters, microstructure, and part properties is essential. Development of such a model requires accounting for the many factors in play during this process, including laser absorption, material addition and melting, fluid flow, various modes of heat transport, and solidification. In this paper, we start with a more modest goal, to create a multiscale model for a specific AM process, Laser Engineered Net Shaping (LENS™), which couples a continuum-level description of a simplified beam melting problem (coupling heat absorption, heat transport, and fluid flow) with a Lattice Boltzmann-cellular automata (LB-CA) microscale model of combined fluid flow, solute transport, and solidification. We apply this model to a binary Ti-5.5 wt pct W alloy and compare calculated quantities, such as dendrite arm spacing, with experimental results reported in a companion paper.

Materials Testing and Cost Modeling for Composite Parts Through Additive Manufacturing

DTIC Science & Technology

2016-04-30

FDM include plastic jet printing (PJP), fused filament modeling ( FFM ), and fused filament fabrication (FFF). FFF was coined by the RepRap project to...additive manufacturing processes? • Fused deposition modeling (FDM) trademarked by Stratasys • Fused filament modeling ( FFM ) and fused filament

NB-PLC channel modelling with cyclostationary noise addition & OFDM implementation for smart grid

NASA Astrophysics Data System (ADS)

Thomas, Togis; Gupta, K. K.

2016-03-01

Power line communication (PLC) technology can be a viable solution for the future ubiquitous networks because it provides a cheaper alternative to other wired technology currently being used for communication. In smart grid Power Line Communication (PLC) is used to support communication with low rate on low voltage (LV) distribution network. In this paper, we propose the channel modelling of narrowband (NB) PLC in the frequency range 5 KHz to 500 KHz by using ABCD parameter with cyclostationary noise addition. Behaviour of the channel was studied by the addition of 11KV/230V transformer, by varying load location and load. Bit error rate (BER) Vs signal to noise ratio SNR) was plotted for the proposed model by employing OFDM. Our simulation results based on the proposed channel model show an acceptable performance in terms of bit error rate versus signal to noise ratio, which enables communication required for smart grid applications.

Applying Additive Hazards Models for Analyzing Survival in Patients with Colorectal Cancer in Fars Province, Southern Iran

PubMed

Madadizadeh, Farzan; Ghanbarnejad, Amin; Ghavami, Vahid; Zare Bandamiri, Mohammad; Mohammadianpanah, Mohammad

2017-04-01

Introduction: Colorectal cancer (CRC) is a commonly fatal cancer that ranks as third worldwide and third and the fifth in Iranian women and men, respectively. There are several methods for analyzing time to event data. Additive hazards regression models take priority over the popular Cox proportional hazards model if the absolute hazard (risk) change instead of hazard ratio is of primary concern, or a proportionality assumption is not made. Methods: This study used data gathered from medical records of 561 colorectal cancer patients who were admitted to Namazi Hospital, Shiraz, Iran, during 2005 to 2010 and followed until December 2015. The nonparametric Aalen’s additive hazards model, semiparametric Lin and Ying’s additive hazards model and Cox proportional hazards model were applied for data analysis. The proportionality assumption for the Cox model was evaluated with a test based on the Schoenfeld residuals and for test goodness of fit in additive models, Cox-Snell residual plots were used. Analyses were performed with SAS 9.2 and R3.2 software. Results: The median follow-up time was 49 months. The five-year survival rate and the mean survival time after cancer diagnosis were 59.6% and 68.1±1.4 months, respectively. Multivariate analyses using Lin and Ying’s additive model and the Cox proportional model indicated that the age of diagnosis, site of tumor, stage, and proportion of positive lymph nodes, lymphovascular invasion and type of treatment were factors affecting survival of the CRC patients. Conclusion: Additive models are suitable alternatives to the Cox proportionality model if there is interest in evaluation of absolute hazard change, or no proportionality assumption is made. Creative Commons Attribution License

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

PubMed Central

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

2013-01-01

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

Modelling of additive manufacturing processes: a review and classification

NASA Astrophysics Data System (ADS)

Stavropoulos, Panagiotis; Foteinopoulos, Panagis

2018-03-01

Additive manufacturing (AM) is a very promising technology; however, there are a number of open issues related to the different AM processes. The literature on modelling the existing AM processes is reviewed and classified. A categorization of the different AM processes in process groups, according to the process mechanism, has been conducted and the most important issues are stated. Suggestions are made as to which approach is more appropriate according to the key performance indicator desired to be modelled and a discussion is included as to the way that future modelling work can better contribute to improving today's AM process understanding.

CREATION OF THE MODEL ADDITIONAL PROTOCOL

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

Houck, F.; Rosenthal, M.; Wulf, N.

In 1991, the international nuclear nonproliferation community was dismayed to discover that the implementation of safeguards by the International Atomic Energy Agency (IAEA) under its NPT INFCIRC/153 safeguards agreement with Iraq had failed to detect Iraq's nuclear weapon program. It was now clear that ensuring that states were fulfilling their obligations under the NPT would require not just detecting diversion but also the ability to detect undeclared materials and activities. To achieve this, the IAEA initiated what would turn out to be a five-year effort to reappraise the NPT safeguards system. The effort engaged the IAEA and its Member Statesmore » and led to agreement in 1997 on a new safeguards agreement, the Model Protocol Additional to the Agreement(s) between States and the International Atomic Energy Agency for the Application of Safeguards. The Model Protocol makes explicit that one IAEA goal is to provide assurance of the absence of undeclared nuclear material and activities. The Model Protocol requires an expanded declaration that identifies a State's nuclear potential, empowers the IAEA to raise questions about the correctness and completeness of the State's declaration, and, if needed, allows IAEA access to locations. The information required and the locations available for access are much broader than those provided for under INFCIRC/153. The negotiation was completed in quite a short time because it started with a relatively complete draft of an agreement prepared by the IAEA Secretariat. This paper describes how the Model Protocol was constructed and reviews key decisions that were made both during the five-year period and in the actual negotiation.« less

Bayesian structured additive regression modeling of epidemic data: application to cholera

PubMed Central

2012-01-01

Background A significant interest in spatial epidemiology lies in identifying associated risk factors which enhances the risk of infection. Most studies, however, make no, or limited use of the spatial structure of the data, as well as possible nonlinear effects of the risk factors. Methods We develop a Bayesian Structured Additive Regression model for cholera epidemic data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (MCMC) simulations. The model is applied to cholera epidemic data in the Kumasi Metropolis, Ghana. Proximity to refuse dumps, density of refuse dumps, and proximity to potential cholera reservoirs were modeled as continuous functions; presence of slum settlers and population density were modeled as fixed effects, whereas spatial references to the communities were modeled as structured and unstructured spatial effects. Results We observe that the risk of cholera is associated with slum settlements and high population density. The risk of cholera is equal and lower for communities with fewer refuse dumps, but variable and higher for communities with more refuse dumps. The risk is also lower for communities distant from refuse dumps and potential cholera reservoirs. The results also indicate distinct spatial variation in the risk of cholera infection. Conclusion The study highlights the usefulness of Bayesian semi-parametric regression model analyzing public health data. These findings could serve as novel information to help health planners and policy makers in making effective decisions to control or prevent cholera epidemics. PMID:22866662

An original traffic additional emission model and numerical simulation on a signalized road

NASA Astrophysics Data System (ADS)

Zhu, Wen-Xing; Zhang, Jing-Yu

2017-02-01

Based on VSP (Vehicle Specific Power) model traffic real emissions were theoretically classified into two parts: basic emission and additional emission. An original additional emission model was presented to calculate the vehicle's emission due to the signal control effects. Car-following model was developed and used to describe the traffic behavior including cruising, accelerating, decelerating and idling at a signalized intersection. Simulations were conducted under two situations: single intersection and two adjacent intersections with their respective control policy. Results are in good agreement with the theoretical analysis. It is also proved that additional emission model may be used to design the signal control policy in our modern traffic system to solve the serious environmental problems.

Influence of Polarization on Carbohydrate Hydration: A Comparative Study Using Additive and Polarizable Force Fields.

PubMed

Pandey, Poonam; Mallajosyula, Sairam S

2016-07-14

Carbohydrates are known to closely modulate their surrounding solvent structures and influence solvation dynamics. Spectroscopic investigations studying far-IR regions (below 1000 cm(-1)) have observed spectral shifts in the libration band (around 600 cm(-1)) of water in the presence of monosaccharides and polysaccharides. In this paper, we use molecular dynamics simulations to gain atomistic insight into carbohydrate-water interactions and to specifically highlight the differences between additive (nonpolarizable) and polarizable simulations. A total of six monosaccharide systems, α and β anomers of glucose, galactose, and mannose, were studied using additive and polarizable Chemistry at HARvard Macromolecular Mechanics (CHARMM) carbohydrate force fields. Solvents were modeled using three additive water models TIP3P, TIP4P, and TIP5P in additive simulations and polarizable water model SWM4 in polarizable simulations. The presence of carbohydrate has a significant effect on the microscopic water structure, with the effects being pronounced for proximal water molecules. Notably, disruption of the tetrahedral arrangement of proximal water molecules was observed due to the formation of strong carbohydrate-water hydrogen bonds in both additive and polarizable simulations. However, the inclusion of polarization resulted in significant water-bridge occupancies, improved ordered water structures (tetrahedral order parameter), and longer carbohydrate-water H-bond correlations as compared to those for additive simulations. Additionally, polarizable simulations also allowed the calculation of power spectra from the dipole-dipole autocorrelation function, which corresponds to the IR spectra. From the power spectra, we could identify spectral signatures differentiating the proximal and bulk water structures, which could not be captured from additive simulations.

Computational Process Modeling for Additive Manufacturing (OSU)

NASA Technical Reports Server (NTRS)

Bagg, Stacey; Zhang, Wei

2015-01-01

Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

Modeling the flux of metabolites in the juvenile hormone biosynthesis pathway using generalized additive models and ordinary differential equations.

PubMed

Martínez-Rincón, Raúl O; Rivera-Pérez, Crisalejandra; Diambra, Luis; Noriega, Fernando G

2017-01-01

Juvenile hormone (JH) regulates development and reproductive maturation in insects. The corpora allata (CA) from female adult mosquitoes synthesize fluctuating levels of JH, which have been linked to the ovarian development and are influenced by nutritional signals. The rate of JH biosynthesis is controlled by the rate of flux of isoprenoids in the pathway, which is the outcome of a complex interplay of changes in precursor pools and enzyme levels. A comprehensive study of the changes in enzymatic activities and precursor pool sizes have been previously reported for the mosquito Aedes aegypti JH biosynthesis pathway. In the present studies, we used two different quantitative approaches to describe and predict how changes in the individual metabolic reactions in the pathway affect JH synthesis. First, we constructed generalized additive models (GAMs) that described the association between changes in specific metabolite concentrations with changes in enzymatic activities and substrate concentrations. Changes in substrate concentrations explained 50% or more of the model deviances in 7 of the 13 metabolic steps analyzed. Addition of information on enzymatic activities almost always improved the fitness of GAMs built solely based on substrate concentrations. GAMs were validated using experimental data that were not included when the model was built. In addition, a system of ordinary differential equations (ODE) was developed to describe the instantaneous changes in metabolites as a function of the levels of enzymatic catalytic activities. The results demonstrated the ability of the models to predict changes in the flux of metabolites in the JH pathway, and can be used in the future to design and validate experimental manipulations of JH synthesis.

Optimizing simulated fertilizer additions using a genetic algorithm with a nutrient uptake model

Treesearch

Wendell P. Cropper; N.B. Comerford

2005-01-01

Intensive management of pine plantations in the southeastern coastal plain typically involves weed and pest control, and the addition of fertilizer to meet the high nutrient demand of rapidly growing pines. In this study we coupled a mechanistic nutrient uptake model (SSAND, soil supply and nutrient demand) with a genetic algorithm (GA) in order to estimate the minimum...

On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis.

PubMed

Li, Bing; Chun, Hyonho; Zhao, Hongyu

2014-09-01

We introduce a nonparametric method for estimating non-gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis.

Additive Manufacturing Modeling and Simulation A Literature Review for Electron Beam Free Form Fabrication

NASA Technical Reports Server (NTRS)

Seufzer, William J.

2014-01-01

Additive manufacturing is coming into industrial use and has several desirable attributes. Control of the deposition remains a complex challenge, and so this literature review was initiated to capture current modeling efforts in the field of additive manufacturing. This paper summarizes about 10 years of modeling and simulation related to both welding and additive manufacturing. The goals were to learn who is doing what in modeling and simulation, to summarize various approaches taken to create models, and to identify research gaps. Later sections in the report summarize implications for closed-loop-control of the process, implications for local research efforts, and implications for local modeling efforts.

On an additive partial correlation operator and nonparametric estimation of graphical models.

PubMed

Lee, Kuang-Yao; Li, Bing; Zhao, Hongyu

2016-09-01

We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance.

On an additive partial correlation operator and nonparametric estimation of graphical models

PubMed Central

Li, Bing; Zhao, Hongyu

2016-01-01

Abstract We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance. PMID:29422689

AA9int: SNP Interaction Pattern Search Using Non-Hierarchical Additive Model Set.

PubMed

Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa; Tung, Heng-Yuan; Sellers, Thomas A; Pow-Sang, Julio; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Hamdy, Freddie; Neal, David E; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lu, Yong-Jie; Park, Jong Y

2018-06-07

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. hlin1@lsuhsc.edu. Supplementary data are available at Bioinformatics online.

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.

Thermal Stability of Nanocrystalline Alloys by Solute Additions and A Thermodynamic Modeling

NASA Astrophysics Data System (ADS)

Saber, Mostafa

and alpha → gamma phase transformation in Fe-Ni-Zr alloys. In addition to the experimental study of thermal stabilization of nanocrystalline Fe-Cr-Zr or Fe-Ni-Zr alloys, the thesis presented here developed a new predictive model, applicable to strongly segregating solutes, for thermodynamic stabilization of binary alloys. This model can serve as a benchmark for selecting solute and evaluating the possible contribution of stabilization. Following a regular solution model, both the chemical and elastic strain energy contributions are combined to obtain the mixing enthalpy. The total Gibbs free energy of mixing is then minimized with respect to simultaneous variations in the grain boundary volume fraction and the solute concentration in the grain boundary and the grain interior. The Lagrange multiplier method was used to obtained numerical solutions. Application are given for the temperature dependence of the grain size and the grain boundary solute excess for selected binary system where experimental results imply that thermodynamic stabilization could be operative. This thesis also extends the binary model to a new model for thermodynamic stabilization of ternary nanocrystalline alloys. It is applicable to strongly segregating size-misfit solutes and uses input data available in the literature. In a same manner as the binary model, this model is based on a regular solution approach such that the chemical and elastic strain energy contributions are incorporated into the mixing enthalpy DeltaHmix, and the mixing entropy DeltaSmix is obtained using the ideal solution approximation. The Gibbs mixing free energy Delta Gmix is then minimized with respect to simultaneous variations in grain growth and solute segregation parameters. The Lagrange multiplier method is similarly used to obtain numerical solutions for the minimum Delta Gmix. The temperature dependence of the nanocrystalline grain size and interfacial solute excess can be obtained for selected ternary systems. As

A novel model for through-silicon via (TSV) filling process simulation considering three additives and current density effect

NASA Astrophysics Data System (ADS)

Wang, Fuliang; Zhao, Zhipeng; Wang, Feng; Wang, Yan; Nie, Nantian

2017-12-01

Through-silicon via (TSV) filling by electrochemical deposition is still a challenge for 3D IC packaging, and three-component additive systems (accelerator, suppressor, and leveler) were commonly used in the industry to achieve void-free filling. However, models considering three additive systems and the current density effect have not been fully studied. In this paper, a novel three-component model was developed to study the TSV filling mechanism and process, where the interaction behavior of the three additives (accelerator, suppressor, and leveler) were considered, and the adsorption, desorption, and consumption coefficient of the three additives were changed with the current density. Based on this new model, the three filling types (seam void, ‘V’ shape, and key hole) were simulated under different current density conditions, and the filling results were verified by experiments. The effect of the current density on the copper ion concentration, additives surface coverage, and local current density distribution during the TSV filling process were obtained. Based on the simulation and experimental results, the diffusion-adsorption-desorption-consumption competition behavior between the suppressor, the accelerator, and the leveler were discussed. The filling mechanisms under different current densities were also analyzed.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Patient-specific in vitro models for hemodynamic analysis of congenital heart disease - Additive manufacturing approach.

PubMed

Medero, Rafael; García-Rodríguez, Sylvana; François, Christopher J; Roldán-Alzate, Alejandro

2017-03-21

Non-invasive hemodynamic assessment of total cavopulmonary connection (TCPC) is challenging due to the complex anatomy. Additive manufacturing (AM) is a suitable alternative for creating patient-specific in vitro models for flow measurements using four-dimensional (4D) Flow MRI. These in vitro systems have the potential to serve as validation for computational fluid dynamics (CFD), simulating different physiological conditions. This study investigated three different AM technologies, stereolithography (SLA), selective laser sintering (SLS) and fused deposition modeling (FDM), to determine differences in hemodynamics when measuring flow using 4D Flow MRI. The models were created using patient-specific MRI data from an extracardiac TCPC. These models were connected to a perfusion pump circulating water at three different flow rates. Data was processed for visualization and quantification of velocity, flow distribution, vorticity and kinetic energy. These results were compared between each model. In addition, the flow distribution obtained in vitro was compared to in vivo. The results showed significant difference in velocities measured at the outlets of the models that required internal support material when printing. Furthermore, an ultrasound flow sensor was used to validate flow measurements at the inlets and outlets of the in vitro models. These results were highly correlated to those measured with 4D Flow MRI. This study showed that commercially available AM technologies can be used to create patient-specific vascular models for in vitro hemodynamic studies at reasonable costs. However, technologies that do not require internal supports during manufacturing allow smoother internal surfaces, which makes them better suited for flow analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

A kinetic study of struvite precipitation recycling technology with NaOH/Mg(OH)2 addition.

PubMed

Yu, Rongtai; Ren, Hongqiang; Wang, Yanru; Ding, Lili; Geng, Jingji; Xu, Ke; Zhang, Yan

2013-09-01

Struvite precipitation recycling technology is received wide attention in removal ammonium and phosphate out of wastewater. While past study focused on process efficiency, and less on kinetics. The kinetic study is essential for the design and optimization in the application of struvite precipitation recycling technology. The kinetics of struvite with NaOH/Mg(OH)2 addition were studied by thermogravimetry analysis with three rates (5, 10, 20 °C/min), using Friedman method and Ozawa-Flynn-Wall method, respectively. Degradation process of struvite with NaOH/Mg(OH)2 addition was three steps. The stripping of ammonia from struvite was mainly occurred at the first step. In the first step, the activation energy was about 70 kJ/mol, which has gradually declined as the reaction progress. By model fitting studies, the proper mechanism function for struvite decomposition process with NaOH/Mg(OH)2 addition was revealed. The mechanism function was f(α)=α(α)-(1-α)(n), a Prout-Tompkins nth order (Bna) model. Copyright © 2013 Elsevier Ltd. All rights reserved.

The effect of tailor-made additives on crystal growth of methyl paraben: Experiments and modelling

NASA Astrophysics Data System (ADS)

Cai, Zhihui; Liu, Yong; Song, Yang; Guan, Guoqiang; Jiang, Yanbin

2017-03-01

In this study, methyl paraben (MP) was selected as the model component, and acetaminophen (APAP), p-methyl acetanilide (PMAA) and acetanilide (ACET), which share the similar molecular structure as MP, were selected as the three tailor-made additives to study the effect of tailor-made additives on the crystal growth of MP. HPLC results indicated that the MP crystals induced by the three additives contained MP only. Photographs of the single crystals prepared indicated that the morphology of the MP crystals was greatly changed by the additives, but PXRD and single crystal diffraction results illustrated that the MP crystals were the same polymorph only with different crystal habits, and no new crystal form was found compared with other references. To investigate the effect of the additives on the crystal growth, the interaction between additives and facets was discussed in detail using the DFT methods and MD simulations. The results showed that APAP, PMAA and ACET would be selectively adsorbed on the growth surfaces of the crystal facets, which induced the change in MP crystal habits.

Influence of polymer additive on flow past a hydrofoil: A numerical study

NASA Astrophysics Data System (ADS)

Xiong, Yongliang; Peng, Sai; Yang, Dan; Duan, Juan; Wang, Limin

2018-01-01

Flows of dilute polymer solutions past a hydrofoil (NACA0012) are examined by direct numerical simulation to investigate the modification of the wake pattern due to the addition of polymer. The influence of polymer additive is modeled by the FENE-P model in order to simulate a non-linear modulus of elasticity and a finite extendibility of the polymer macromolecules. Simulations were carried out at a Reynolds number of 1000 with the angle of attack varying from 0° to 20°. The results show that the influence of polymer on the flow behavior of the flow past a hydrofoil exhibits different flow regimes. In general, the addition of polymer modifies the wake patterns for all angles of attack in this study. Consequently, both drag and lift forces are changed as the Weissenberg number increases while the drag of the hydrofoil is enhanced at small angles of attack and reduced at large angles of attack. As the Weissenberg number increases, two attached recirculation bubbles or two columns of shedding vortices downstream tend to be symmetric, and the polymer tends to make the flow less sensitive to the variation of the angle of attack.

Representational Flexibility and Problem-Solving Ability in Fraction and Decimal Number Addition: A Structural Model

ERIC Educational Resources Information Center

Deliyianni, Eleni; Gagatsis, Athanasios; Elia, Iliada; Panaoura, Areti

2016-01-01

The aim of this study was to propose and validate a structural model in fraction and decimal number addition, which is founded primarily on a synthesis of major theoretical approaches in the field of representations in Mathematics and also on previous research on the learning of fractions and decimals. The study was conducted among 1,701 primary…

Quantile regression via vector generalized additive models.

PubMed

Yee, Thomas W

2004-07-30

One of the most popular methods for quantile regression is the LMS method of Cole and Green. The method naturally falls within a penalized likelihood framework, and consequently allows for considerable flexible because all three parameters may be modelled by cubic smoothing splines. The model is also very understandable: for a given value of the covariate, the LMS method applies a Box-Cox transformation to the response in order to transform it to standard normality; to obtain the quantiles, an inverse Box-Cox transformation is applied to the quantiles of the standard normal distribution. The purposes of this article are three-fold. Firstly, LMS quantile regression is presented within the framework of the class of vector generalized additive models. This confers a number of advantages such as a unifying theory and estimation process. Secondly, a new LMS method based on the Yeo-Johnson transformation is proposed, which has the advantage that the response is not restricted to be positive. Lastly, this paper describes a software implementation of three LMS quantile regression methods in the S language. This includes the LMS-Yeo-Johnson method, which is estimated efficiently by a new numerical integration scheme. The LMS-Yeo-Johnson method is illustrated by way of a large cross-sectional data set from a New Zealand working population. Copyright 2004 John Wiley & Sons, Ltd.

Study on thermal effects & sulfurized additives, in lubricating greases

NASA Astrophysics Data System (ADS)

Shah, Ami Atul

Lithium Base grease constitutes about 50% of market. The greases are developed to be able to work in multiple working conditions and have longer working life. Greases with extreme pressure additives and anti-wear additives have been developed as a solution to many of the applications. These developed greases are tested under ASTM D2266 testing conditions to meet the requirements. The actual working conditions, although, differ than the real testing conditions. The loading, speed and temperature conditions can be more harsh, or fluctuating in nature. The cyclic nature of the parameters cannot be directly related to the test performance. For this purpose studies on the performance under spectrum loading, variable speed and fluctuating temperature must be performed. This study includes tests to understand the effect of thermal variation on some of the most commonly used grease additives that perform well under ASTM D2266 testing conditions. The studied additives include most widely used industrial extreme pressure additive MoS2. Performance of ZDDP which is trying to replace MoS2 in its industrial applications has also been studied. The tests cover study of extreme pressure, anti-wear and friction modifier additives to get a general idea on the effects of thermal variation in three areas. Sulphur is the most common extreme pressure additive. Sulphur based MoS 2 is extensively used grease additive. Study to understand the tribological performance of this additive through wear testing and SEM/EDX studies has been done. This performance is also studied for other metallic sulfides like WS2 and sulphur based organic compound. The aim is to study the importance of the type of bond that sulphur shares in its additive's structure on its performance. The MoS2 film formation is found to be on the basis of the FeS formation on the substrate and protection through sacrificial monolayer deposition of the MoS2 sheared structure. The free Mo then tends to oxidise. An attempt to

Network Reconstruction Using Nonparametric Additive ODE Models

PubMed Central

Henderson, James; Michailidis, George

2014-01-01

Network representations of biological systems are widespread and reconstructing unknown networks from data is a focal problem for computational biologists. For example, the series of biochemical reactions in a metabolic pathway can be represented as a network, with nodes corresponding to metabolites and edges linking reactants to products. In a different context, regulatory relationships among genes are commonly represented as directed networks with edges pointing from influential genes to their targets. Reconstructing such networks from data is a challenging problem receiving much attention in the literature. There is a particular need for approaches tailored to time-series data and not reliant on direct intervention experiments, as the former are often more readily available. In this paper, we introduce an approach to reconstructing directed networks based on dynamic systems models. Our approach generalizes commonly used ODE models based on linear or nonlinear dynamics by extending the functional class for the functions involved from parametric to nonparametric models. Concomitantly we limit the complexity by imposing an additive structure on the estimated slope functions. Thus the submodel associated with each node is a sum of univariate functions. These univariate component functions form the basis for a novel coupling metric that we define in order to quantify the strength of proposed relationships and hence rank potential edges. We show the utility of the method by reconstructing networks using simulated data from computational models for the glycolytic pathway of Lactocaccus Lactis and a gene network regulating the pluripotency of mouse embryonic stem cells. For purposes of comparison, we also assess reconstruction performance using gene networks from the DREAM challenges. We compare our method to those that similarly rely on dynamic systems models and use the results to attempt to disentangle the distinct roles of linearity, sparsity, and derivative

GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis.

PubMed

Stricker, Georg; Engelhardt, Alexander; Schulz, Daniel; Schmid, Matthias; Tresch, Achim; Gagneur, Julien

2017-08-01

Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays. Software is available from Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/GenoGAM.html . gagneur@in.tum.de. Supplementary information is available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The potential application of European market research data in dietary exposure modelling of food additives.

PubMed

Tennant, David Robin; Bruyninckx, Chris

2018-03-01

Consumer exposure assessments for food additives are incomplete without information about the proportions of foods in each authorised category that contain the additive. Such information has been difficult to obtain but the Mintel Global New Products Database (GNPD) provides information about product launches across Europe over the past 20 years. These data can be searched to identify products with specific additives listed on product labels and the numbers compared with total product launches for food and drink categories in the same database to determine the frequency of occurrence. There are uncertainties associated with the data but these can be managed by adopting a cautious and conservative approach. GNPD data can be mapped with authorised food categories and with food descriptions used in the EFSA Comprehensive European Food Consumption Surveys Database for exposure modelling. The data, when presented as percent occurrence, could be incorporated into the EFSA ANS Panel's 'brand-loyal/non-brand loyal exposure model in a quantitative way. Case studies of preservative, antioxidant, colour and sweetener additives showed that the impact of including occurrence data is greatest in the non-brand loyal scenario. Recommendations for future research include identifying occurrence data for alcoholic beverages, linking regulatory food codes, FoodEx and GNPD product descriptions, developing the use of occurrence data for carry-over foods and improving understanding of brand loyalty in consumer exposure models.

Statistical inference for the additive hazards model under outcome-dependent sampling.

PubMed

Yu, Jichang; Liu, Yanyan; Sandler, Dale P; Zhou, Haibo

2015-09-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer.

Statistical inference for the additive hazards model under outcome-dependent sampling

PubMed Central

Yu, Jichang; Liu, Yanyan; Sandler, Dale P.; Zhou, Haibo

2015-01-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer. PMID:26379363

Meta-analysis of high-latitude nitrogen-addition and warming studies imply ecological mechanisms overlooked by land models

NASA Astrophysics Data System (ADS)

Bouskill, N. J.; Riley, W. J.; Tang, J.

2014-08-01

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differed from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.

Meta-analysis of high-latitude nitrogen-addition and warming studies imply ecological mechanisms overlooked by land models

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

Bouskill, N. J.; Riley, W. J.; Tang, J.

2014-08-18

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differedmore » from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha -1 yr -1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.« less

Regression analysis of informative current status data with the additive hazards model.

PubMed

Zhao, Shishun; Hu, Tao; Ma, Ling; Wang, Peijie; Sun, Jianguo

2015-04-01

This paper discusses regression analysis of current status failure time data arising from the additive hazards model in the presence of informative censoring. Many methods have been developed for regression analysis of current status data under various regression models if the censoring is noninformative, and also there exists a large literature on parametric analysis of informative current status data in the context of tumorgenicity experiments. In this paper, a semiparametric maximum likelihood estimation procedure is presented and in the method, the copula model is employed to describe the relationship between the failure time of interest and the censoring time. Furthermore, I-splines are used to approximate the nonparametric functions involved and the asymptotic consistency and normality of the proposed estimators are established. A simulation study is conducted and indicates that the proposed approach works well for practical situations. An illustrative example is also provided.

Metal Big Area Additive Manufacturing: Process Modeling and Validation

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

Simunovic, Srdjan; Nycz, Andrzej; Noakes, Mark W

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology for printing large-scale 3D objects. mBAAM is based on the gas metal arc welding process and uses a continuous feed of welding wire to manufacture an object. An electric arc forms between the wire and the substrate, which melts the wire and deposits a bead of molten metal along the predetermined path. In general, the welding process parameters and local conditions determine the shape of the deposited bead. The sequence of the bead deposition and the corresponding thermal history of the manufactured object determine the long rangemore » effects, such as thermal-induced distortions and residual stresses. Therefore, the resulting performance or final properties of the manufactured object are dependent on its geometry and the deposition path, in addition to depending on the basic welding process parameters. Physical testing is critical for gaining the necessary knowledge for quality prints, but traversing the process parameter space in order to develop an optimized build strategy for each new design is impractical by pure experimental means. Computational modeling and optimization may accelerate development of a build process strategy and saves time and resources. Because computational modeling provides these opportunities, we have developed a physics-based Finite Element Method (FEM) simulation framework and numerical models to support the mBAAM process s development and design. In this paper, we performed a sequentially coupled heat transfer and stress analysis for predicting the final deformation of a small rectangular structure printed using the mild steel welding wire. Using the new simulation technologies, material was progressively added into the FEM simulation as the arc weld traversed the build path. In the sequentially coupled heat transfer and stress analysis, the heat transfer was performed to calculate the temperature evolution, which was used in a stress

Dinuclear Tricyclic Transition State Model for Carbonyl Addition of Organotitanium Reagents: DFT Study on the Activity and Enantioselectivity of BINOLate Titanium Catalysts.

PubMed

Harada, Toshiro

2018-06-08

In the presence of a catalytic amount of chiral BINOL derivatives (or BINOLs), a mixture of various organometallic compounds with Ti(O i Pr) 4 undergoes enantioselective addition to aldehydes and ketones. Although the catalyst and reacting nucleophile of the reaction have been elucidated to be ( BINOLate)Ti 2 (O i Pr) 6 and RTi(O i Pr) 3 , respectively, little is known about the properties of short-lived intermediates and transition structures. In this work, the mechanism of this reaction is investigated with the aid of DFT (M06) calculations. The study provides support for the following mechanistic understandings: (i) The direct racemic reaction proceeds through a pathway involving initial aggregation of RTi(O i Pr) 3 with Ti(O i Pr) 4 followed by carbonyl addition of the resulting dinuclear aggregate. (ii) The enantioselective reaction takes place through a pathway involving initial ligand exchange of RTi(O i Pr) 3 with ( BINOLate)Ti 2 (O i Pr) 6 followed by the addition of the resulting chiral dinuclear titanium species via a chiral BINOLate-chelated, tricyclic transition structure. (iii) The enantioselective pathway is favorable not because BINOLate ligands accelerate the carbonyl addition but because the ligands stabilize the chiral dinuclear species against deaggregation through a chelating bridge. (iv) The chiral transition structure serves as a model accounting for the re-face addition generally observed in the reaction of aldehydes with ( R)- BINOLs.

Additive-induced aggregate changes of two structurally similar dyes in aqueous solutions: A comparative photophysical study

NASA Astrophysics Data System (ADS)

Ghanadzadeh Gilani, A.; Poormohammadi-Ahandani, Z.; Kian, R.

2018-01-01

Absorption and emission spectral characteristics of the two structurally similar phenothiazine dyes, azure B and toluidine blue, in aqueous solutions of the two sets of molecular additives (ureas and monosaccharides) were studied as a function of the dye and additive concentrations. The absorption spectra of the dyes were also studied in pure tetramethylurea with an aprotic nature. The spectral data were analyzed using DECOM Program. The dimer structure of the interacting molecules in these dyes was discussed using the exciton model. The urea class of additives was found to act as water structure-breakers over the range of studied concentration. The carbohydrate additives were found to act as water structure-breakers at low concentrations. However, the water structure breaking process may be disfavored by the additive-additive interactions at higher concentrations. It can be concluded that at low additive concentrations, the main driving force for breaking the dye association is water-additive interaction, which disrupts the water hydrogen bonds induced by the additives. However, at the high additive concentrations, the different phenomena including additive-additive and additive-dye interactions can change the structure, strength, and aggregative properties of the dyes. Finally, the urea in water induces noticeably fluorescence quenching in emission spectra of both the dyes.

Additive-induced aggregate changes of two structurally similar dyes in aqueous solutions: A comparative photophysical study.

PubMed

Ghanadzadeh Gilani, A; Poormohammadi-Ahandani, Z; Kian, R

2018-01-15

Absorption and emission spectral characteristics of the two structurally similar phenothiazine dyes, azure B and toluidine blue, in aqueous solutions of the two sets of molecular additives (ureas and monosaccharides) were studied as a function of the dye and additive concentrations. The absorption spectra of the dyes were also studied in pure tetramethylurea with an aprotic nature. The spectral data were analyzed using DECOM Program. The dimer structure of the interacting molecules in these dyes was discussed using the exciton model. The urea class of additives was found to act as water structure-breakers over the range of studied concentration. The carbohydrate additives were found to act as water structure-breakers at low concentrations. However, the water structure breaking process may be disfavored by the additive-additive interactions at higher concentrations. It can be concluded that at low additive concentrations, the main driving force for breaking the dye association is water-additive interaction, which disrupts the water hydrogen bonds induced by the additives. However, at the high additive concentrations, the different phenomena including additive-additive and additive-dye interactions can change the structure, strength, and aggregative properties of the dyes. Finally, the urea in water induces noticeably fluorescence quenching in emission spectra of both the dyes. Copyright © 2017 Elsevier B.V. All rights reserved.

Aggregation of gluten proteins in model dough after fibre polysaccharide addition.

PubMed

Nawrocka, Agnieszka; Szymańska-Chargot, Monika; Miś, Antoni; Wilczewska, Agnieszka Z; Markiewicz, Karolina H

2017-09-15

FT-Raman spectroscopy, thermogravimetry and differential scanning calorimetry were used to study changes in structure of gluten proteins and their thermal properties influenced by four dietary fibre polysaccharides (microcrystalline cellulose, inulin, apple pectin and citrus pectin) during development of a model dough. The flour reconstituted from wheat starch and wheat gluten was mixed with the polysaccharides in five concentrations: 3%, 6%, 9%, 12% and 18%. The obtained results showed that all polysaccharides induced similar changes in secondary structure of gluten proteins concerning formation of aggregates (1604cm -1 ), H-bonded parallel- and antiparallel-β-sheets (1690cm -1 ) and H-bonded β-turns (1664cm -1 ). These changes concerned mainly glutenins since β-structures are characteristic for them. The observed structural changes confirmed hypothesis about partial dehydration of gluten network after polysaccharides addition. The gluten aggregation and dehydration processes were also reflected in the DSC results, while the TGA ones showed that gluten network remained thermally stable after polysaccharides addition. Copyright © 2017 Elsevier Ltd. All rights reserved.

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models

PubMed Central

Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens

2016-01-01

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials. This article is part of the themed issue ‘Evolutionary ecology of arthropod antimicrobial peptides’. PMID:27160596

Mixed Model Methods for Genomic Prediction and Variance Component Estimation of Additive and Dominance Effects Using SNP Markers

PubMed Central

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005–0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level. PMID:24498162

Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

PubMed

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005-0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level.

Guarana Provides Additional Stimulation over Caffeine Alone in the Planarian Model

PubMed Central

Moustakas, Dimitrios; Mezzio, Michael; Rodriguez, Branden R.; Constable, Mic Andre; Mulligan, Margaret E.; Voura, Evelyn B.

2015-01-01

The stimulant effect of energy drinks is primarily attributed to the caffeine they contain. Many energy drinks also contain other ingredients that might enhance the tonic effects of these caffeinated beverages. One of these additives is guarana. Guarana is a climbing plant native to the Amazon whose seeds contain approximately four times the amount of caffeine found in coffee beans. The mix of other natural chemicals contained in guarana seeds is thought to heighten the stimulant effects of guarana over caffeine alone. Yet, despite the growing use of guarana as an additive in energy drinks, and a burgeoning market for it as a nutritional supplement, the science examining guarana and how it affects other dietary ingredients is lacking. To appreciate the stimulant effects of guarana and other natural products, a straightforward model to investigate their physiological properties is needed. The planarian provides such a system. The locomotor activity and convulsive response of planarians with substance exposure has been shown to provide an excellent system to measure the effects of drug stimulation, addiction and withdrawal. To gauge the stimulant effects of guarana we studied how it altered the locomotor activity of the planarian species Dugesia tigrina. We report evidence that guarana seeds provide additional stimulation over caffeine alone, and document the changes to this stimulation in the context of both caffeine and glucose. PMID:25880065

Adsorption of molecular additive onto lead halide perovskite surfaces: A computational study on Lewis base thiophene additive passivation

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yu, Fengxi; Chen, Lihong; Li, Jingfa

2018-06-01

Organic additives, such as the Lewis base thiophene, have been successfully applied to passivate halide perovskite surfaces, improving the stability and properties of perovskite devices based on CH3NH3PbI3. Yet, the detailed nanostructure of the perovskite surface passivated by additives and the mechanisms of such passivation are not well understood. This study presents a nanoscopic view on the interfacial structure of an additive/perovskite interface, consisting of a Lewis base thiophene molecular additive and a lead halide perovskite surface substrate, providing insights on the mechanisms that molecular additives can passivate the halide perovskite surfaces and enhance the perovskite-based device performance. Molecular dynamics study on the interactions between water molecules and the perovskite surfaces passivated by the investigated additive reveal the effectiveness of employing the molecular additives to improve the stability of the halide perovskite materials. The additive/perovskite surface system is further probed via molecular engineering the perovskite surfaces. This study reveals the nanoscopic structure-property relationships of the halide perovskite surface passivated by molecular additives, which helps the fundamental understanding of the surface/interface engineering strategies for the development of halide perovskite based devices.

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review.

PubMed

Savio, Gianpaolo; Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

2018-01-01

Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed.

The use of generalised additive models (GAM) in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1997-12-01

Ordinary multiple regression and logistic multiple regression are widely applied statistical methods which allow a researcher to 'explain' or 'predict' a response variable from a set of explanatory variables or predictors. In these models it is usually assumed that quantitative predictors such as age enter linearly into the model. During recent years these methods have been further developed to allow more flexibility in the way explanatory variables 'act' on a response variable. The methods are called 'generalised additive models' (GAM). The rigid linear terms characterising the association between response and predictors are replaced in an optimal way by flexible curved functions of the predictors (the 'profiles'). Plotting the 'profiles' allows the researcher to visualise easily the shape by which predictors 'act' over the whole range of values. The method facilitates detection of particular shapes such as 'bumps', 'U-shapes', 'J-shapes, 'threshold values' etc. Information about the shape of the association is not revealed by traditional methods. The shapes of the profiles may be checked by performing a Monte Carlo simulation ('bootstrapping'). After the presentation of the GAM a relevant case study is presented in order to demonstrate application and use of the method. The dependence of caries in primary teeth on a set of explanatory variables is investigated. Since GAMs may not be easily accessible to dentists, this article presents them in an introductory condensed form. It was thought that a nonmathematical summary and a worked example might encourage readers to consider the methods described. GAMs may be of great value to dentists in allowing visualisation of the shape by which predictors 'act' and obtaining a better understanding of the complex relationships between predictors and response.

Development of a QTL-environment-based predictive model for node addition rate in common bean.

PubMed

Zhang, Li; Gezan, Salvador A; Eduardo Vallejos, C; Jones, James W; Boote, Kenneth J; Clavijo-Michelangeli, Jose A; Bhakta, Mehul; Osorno, Juan M; Rao, Idupulapati; Beebe, Stephen; Roman-Paoli, Elvin; Gonzalez, Abiezer; Beaver, James; Ricaurte, Jaumer; Colbert, Raphael; Correll, Melanie J

2017-05-01

This work reports the effects of the genetic makeup, the environment and the genotype by environment interactions for node addition rate in an RIL population of common bean. This information was used to build a predictive model for node addition rate. To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day - 1 ) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50-90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions.

Model for Assembly Line Re-Balancing Considering Additional Capacity and Outsourcing to Face Demand Fluctuations

NASA Astrophysics Data System (ADS)

Samadhi, TMAA; Sumihartati, Atin

2016-02-01

The most critical stage in a garment industry is sewing process, because generally, it consists of a number of operations and a large number of sewing machines for each operation. Therefore, it requires a balancing method that can assign task to work station with balance workloads. Many studies on assembly line balancing assume a new assembly line, but in reality, due to demand fluctuation and demand increased a re-balancing is needed. To cope with those fluctuating demand changes, additional capacity can be carried out by investing in spare sewing machine and paying for sewing service through outsourcing. This study develops an assembly line balancing (ALB) model on existing line to cope with fluctuating demand change. Capacity redesign is decided if the fluctuation demand exceeds the available capacity through a combination of making investment on new machines and outsourcing while considering for minimizing the cost of idle capacity in the future. The objective of the model is to minimize the total cost of the line assembly that consists of operating costs, machine cost, adding capacity cost, losses cost due to idle capacity and outsourcing costs. The model develop is based on an integer programming model. The model is tested for a set of data of one year demand with the existing number of sewing machines of 41 units. The result shows that additional maximum capacity up to 76 units of machine required when there is an increase of 60% of the average demand, at the equal cost parameters..

Process Modeling and Validation for Metal Big Area Additive Manufacturing

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

Simunovic, Srdjan; Nycz, Andrzej; Noakes, Mark W.

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology based on the metal arc welding. A continuously fed metal wire is melted by an electric arc that forms between the wire and the substrate, and deposited in the form of a bead of molten metal along the predetermined path. Objects are manufactured one layer at a time starting from the base plate. The final properties of the manufactured object are dependent on its geometry and the metal deposition path, in addition to depending on the basic welding process parameters. Computational modeling can be used to acceleratemore » the development of the mBAAM technology as well as a design and optimization tool for the actual manufacturing process. We have developed a finite element method simulation framework for mBAAM using the new features of software ABAQUS. The computational simulation of material deposition with heat transfer is performed first, followed by the structural analysis based on the temperature history for predicting the final deformation and stress state. In this formulation, we assume that two physics phenomena are coupled in only one direction, i.e. the temperatures are driving the deformation and internal stresses, but their feedback on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.« less

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

PubMed Central

Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

2018-01-01

Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed. PMID:29487626

Supra-additive effects of tramadol and acetaminophen in a human pain model.

PubMed

Filitz, Jörg; Ihmsen, Harald; Günther, Werner; Tröster, Andreas; Schwilden, Helmut; Schüttler, Jürgen; Koppert, Wolfgang

2008-06-01

The combination of analgesic drugs with different pharmacological properties may show better efficacy with less side effects. Aim of this study was to examine the analgesic and antihyperalgesic properties of the weak opioid tramadol and the non-opioid acetaminophen, alone as well as in combination, in an experimental pain model in humans. After approval of the local Ethics Committee, 17 healthy volunteers were enrolled in this double-blind and placebo-controlled study in a cross-over design. Transcutaneous electrical stimulation at high current densities (29.6+/-16.2 mA) induced spontaneous acute pain (NRS=6 of 10) and distinct areas of hyperalgesia for painful mechanical stimuli (pinprick-hyperalgesia). Pain intensities as well as the extent of the areas of hyperalgesia were assessed before, during and 150 min after a 15 min lasting intravenous infusion of acetaminophen (650 mg), tramadol (75 mg), a combination of both (325 mg acetaminophen and 37.5mg tramadol), or saline 0.9%. Tramadol led to a maximum pain reduction of 11.7+/-4.2% with negligible antihyperalgesic properties. In contrast, acetaminophen led to a similar pain reduction (9.8+/-4.4%), but a sustained antihyperalgesic effect (34.5+/-14.0% reduction of hyperalgesic area). The combination of both analgesics at half doses led to a supra-additive pain reduction of 15.2+/-5.7% and an enhanced antihyperalgesic effect (41.1+/-14.3% reduction of hyperalgesic areas) as compared to single administration of acetaminophen. Our study provides first results on interactions of tramadol and acetaminophen on experimental pain and hyperalgesia in humans. Pharmacodynamic modeling combined with the isobolographic technique showed supra-additive effects of the combination of acetaminophen and tramadol concerning both, analgesia and antihyperalgesia. The results might act as a rationale for combining both analgesics.

Effect of Additional Incentives for Aviation Biofuels: Results from the Biomass Scenario Model

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

Vimmerstedt, Laura J; Newes, Emily K

2017-12-05

The National Renewable Energy Laboratory supported the Department of Energy, Bioenergy Technologies Office, with analysis of alternative jet fuels in collaboration with the U.S. Department of Transportation, Federal Aviation Administration. Airlines for America requested additional exploratory scenarios within FAA analytic framework. Airlines for America requested additional analysis using the same analytic framework, the Biomass Scenario Model. The results were presented at a public working meeting of the California Air Resources Board on including alternative jet fuel in the Low Carbon Fuel Standard on March 17, 2017 (https://www.arb.ca.gov/fuels/lcfs/lcfs_meetings/lcfs_meetings.htm). This presentation clarifies and annotates the slides from the public working meeting, andmore » provides a link to the full data set. NREL does not advocate for or against the policies analyzed in this study.« less

Effect of Additional Incentives for Aviation Biofuels: Results from the Biomass Scenario Model

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

Vimmerstedt, Laura J; Newes, Emily K

The National Renewable Energy Laboratory supported the Department of Energy, Bioenergy Technologies Office, with analysis of alternative jet fuels in collaboration with the U.S. Department of Transportation, Federal Aviation Administration. Airlines for America requested additional exploratory scenarios within FAA analytic framework. Airlines for America requested additional analysis using the same analytic framework, the Biomass Scenario Model. The results were presented at a public working meeting of the California Air Resources Board on including alternative jet fuel in the Low Carbon Fuel Standard on March 17, 2017 (https://www.arb.ca.gov/fuels/lcfs/lcfs_meetings/lcfs_meetings.htm). This presentation clarifies and annotates the slides from the public working meeting, andmore » provides a link to the full data set. NREL does not advocate for or against the policies analyzed in this study.« less

Evaluation of 3D Additively Manufactured Canine Brain Models for Teaching Veterinary Neuroanatomy.

PubMed

Schoenfeld-Tacher, Regina M; Horn, Timothy J; Scheviak, Tyler A; Royal, Kenneth D; Hudson, Lola C

Physical specimens are essential to the teaching of veterinary anatomy. While fresh and fixed cadavers have long been the medium of choice, plastinated specimens have gained widespread acceptance as adjuncts to dissection materials. Even though the plastination process increases the durability of specimens, these are still derived from animal tissues and require periodic replacement if used by students on a regular basis. This study investigated the use of three-dimensional additively manufactured (3D AM) models (colloquially referred to as 3D-printed models) of the canine brain as a replacement for plastinated or formalin-fixed brains. The models investigated were built based on a micro-MRI of a single canine brain and have numerous practical advantages, such as durability, lower cost over time, and reduction of animal use. The effectiveness of the models was assessed by comparing performance among students who were instructed using either plastinated brains or 3D AM models. This study used propensity score matching to generate similar pairs of students. Pairings were based on gender and initial anatomy performance across two consecutive classes of first-year veterinary students. Students' performance on a practical neuroanatomy exam was compared, and no significant differences were found in scores based on the type of material (3D AM models or plastinated specimens) used for instruction. Students in both groups were equally able to identify neuroanatomical structures on cadaveric material, as well as respond to questions involving application of neuroanatomy knowledge. Therefore, we postulate that 3D AM canine brain models are an acceptable alternative to plastinated specimens in teaching veterinary neuroanatomy.

Low-molecular-weight model study of peroxide cross-linking of ethylene-propylene-diene rubber using gas chromatography and mass spectrometry II. Addition and combination reactions.

PubMed

Peters, R; van Duin, M; Tonoli, D; Kwakkenbos, G; Mengerink, Y; van Benthem, R A T M; de Koster, C G; Schoenmakers, P J; van der Wal, Sj

2008-08-08

The dicumyl-peroxide-initiated addition and combination reactions of mixtures of alkanes (n-octane, n-decane) and alkenes [5,6-dihydrodicyclopentadiene (DCPDH), 5-ethylidene-2-norbornane (ENBH) and 5-vinylidene-2-norbornane (VNBH)] were studied to mimic the peroxide cross-linking reactions of terpolymerised ethylene, propylene and a diene monomer (EPDM). The reaction products of the mixtures were separated by both gas chromatography (GC) and comprehensive two-dimensional gas chromatography (GCxGC). The separated compounds were identified from their mass spectra and their GC and GCxGC elution pattern. Quantification of the various alkyl/alkyl, alkyl/allyl and allyl/allyl combination products shows that allylic-radicals comprise approximately 60% of the substrate radicals formed. The total concentration of the products formed by combination is found to be independent of the concentration and the type of alkene. The total concentration of the products formed by addition to the alkene increases with increasing concentration of alkene. In addition, the total concentration of the formed addition products depends strongly on the type of the alkene used, viz. VNBH>ENBH approximately DCPDH, which is a consequence of differences in steric hindrance of the unsaturation. The peroxide curing efficiency, defined as the number of moles of cross-linked products formed per mol of peroxide, is 173% using 9% (w/w) 5-vinylidene-2-norbornane (VNBH). This indicates that the addition reaction is recurrent. All these findings are consistent with experimental studies on peroxide curing of EPDM rubber. In addition, the present results provide more-detailed structural information, increasing the understanding of the mechanism of peroxide curing of EPDM. The described approach to use low-molecular-weight model compounds followed by GC-mass spectrometry (MS) and GCxGC-MS analysis is proven to be a very powerful tool to study the cross-linking of EPDM.

An Analysis of Kindergarten and First Grade Children's Addition and Subtraction Problem Solving Modeling and Accuracy.

ERIC Educational Resources Information Center

Shores, Jay H.; Underhill, Robert G.

A study was undertaken of the effects of formal education and conservation of numerousness on addition and subtraction problem types. Thirty-six kindergarten and 36 first-grade subjects randomly selected from one area of a school district were administered measures of conservation, problem-solving success, and modeling ability. Following factor…

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling.

PubMed

Thelen, Brian; French, Nancy H F; Koziol, Benjamin W; Billmire, Michael; Owen, Robert Chris; Johnson, Jeffrey; Ginsberg, Michele; Loboda, Tatiana; Wu, Shiliang

2013-11-05

A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. The model developed in this study allows a

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling

PubMed Central

2013-01-01

Background A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Methods Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. Results The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. Conclusions The

Reduction of carcinogenic 4(5)-methylimidazole in a caramel model system: influence of food additives.

PubMed

Seo, Seulgi; Ka, Mi-Hyun; Lee, Kwang-Geun

2014-07-09

The effect of various food additives on the formation of carcinogenic 4(5)-methylimidazole (4-MI) in a caramel model system was investigated. The relationship between the levels of 4-MI and various pyrazines was studied. When glucose and ammonium hydroxide were heated, the amount of 4-MI was 556 ± 1.3 μg/mL, which increased to 583 ± 2.6 μg/mL by the addition of 0.1 M of sodium sulfite. When various food additives, such as 0.1 M of iron sulfate, magnesium sulfate, zinc sulfate, tryptophan, and cysteine were added, the amount of 4-MI was reduced to 110 ± 0.7, 483 ± 2.0, 460 ± 2.0, 409 ± 4.4, and 397 ± 1.7 μg/mL, respectively. The greatest reduction, 80%, occurred with the addition of iron sulfate. Among the 12 pyrazines, 2-ethyl-6-methylpyrazine with 4-MI showed the highest correlation (r = -0.8239).

The Job Demands-Resources Model: An Analysis of Additive and Joint Effects of Demands and Resources

ERIC Educational Resources Information Center

Hu, Qiao; Schaufeli, Wilmar B.; Taris, Toon W.

2011-01-01

The present study investigated the additive, synergistic, and moderating effects of job demands and job resources on well-being (burnout and work engagement) and organizational outcomes, as specified by the Job Demands-Resources (JD-R) model. A survey was conducted among two Chinese samples: 625 blue collar workers and 761 health professionals. A…

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

Diagnostic utility of appetite loss in addition to existing prediction models for community-acquired pneumonia in the elderly: a prospective diagnostic study in acute care hospitals in Japan

PubMed Central

Yamamoto, Yosuke; Terada, Kazuhiko; Ohta, Mitsuyasu; Mikami, Wakako; Yokota, Hajime; Hayashi, Michio; Miyashita, Jun; Azuma, Teruhisa; Fukuma, Shingo; Fukuhara, Shunichi

2017-01-01

Objective Diagnosis of community-acquired pneumonia (CAP) in the elderly is often delayed because of atypical presentation and non-specific symptoms, such as appetite loss, falls and disturbance in consciousness. The aim of this study was to investigate the external validity of existing prediction models and the added value of the non-specific symptoms for the diagnosis of CAP in elderly patients. Design Prospective cohort study. Setting General medicine departments of three teaching hospitals in Japan. Participants A total of 109 elderly patients who consulted for upper respiratory symptoms between 1 October 2014 and 30 September 2016. Main outcome measures The reference standard for CAP was chest radiograph evaluated by two certified radiologists. The existing models were externally validated for diagnostic performance by calibration plot and discrimination. To evaluate the additional value of the non-specific symptoms to the existing prediction models, we developed an extended logistic regression model. Calibration, discrimination, category-free net reclassification improvement (NRI) and decision curve analysis (DCA) were investigated in the extended model. Results Among the existing models, the model by van Vugt demonstrated the best performance, with an area under the curve of 0.75(95% CI 0.63 to 0.88); calibration plot showed good fit despite a significant Hosmer-Lemeshow test (p=0.017). Among the non-specific symptoms, appetite loss had positive likelihood ratio of 3.2 (2.0–5.3), negative likelihood ratio of 0.4 (0.2–0.7) and OR of 7.7 (3.0–19.7). Addition of appetite loss to the model by van Vugt led to improved calibration at p=0.48, NRI of 0.53 (p=0.019) and higher net benefit by DCA. Conclusions Information on appetite loss improved the performance of an existing model for the diagnosis of CAP in the elderly. PMID:29122806

A habitat suitability model for Chinese sturgeon determined using the generalized additive method

NASA Astrophysics Data System (ADS)

Yi, Yujun; Sun, Jie; Zhang, Shanghong

2016-03-01

The Chinese sturgeon is a type of large anadromous fish that migrates between the ocean and rivers. Because of the construction of dams, this sturgeon's migration path has been cut off, and this species currently is on the verge of extinction. Simulating suitable environmental conditions for spawning followed by repairing or rebuilding its spawning grounds are effective ways to protect this species. Various habitat suitability models based on expert knowledge have been used to evaluate the suitability of spawning habitat. In this study, a two-dimensional hydraulic simulation is used to inform a habitat suitability model based on the generalized additive method (GAM). The GAM is based on real data. The values of water depth and velocity are calculated first via the hydrodynamic model and later applied in the GAM. The final habitat suitability model is validated using the catch per unit effort (CPUEd) data of 1999 and 2003. The model results show that a velocity of 1.06-1.56 m/s and a depth of 13.33-20.33 m are highly suitable ranges for the Chinese sturgeon to spawn. The hydraulic habitat suitability indexes (HHSI) for seven discharges (4000; 9000; 12,000; 16,000; 20,000; 30,000; and 40,000 m3/s) are calculated to evaluate integrated habitat suitability. The results show that the integrated habitat suitability reaches its highest value at a discharge of 16,000 m3/s. This study is the first to apply a GAM to evaluate the suitability of spawning grounds for the Chinese sturgeon. The study provides a reference for the identification of potential spawning grounds in the entire basin.

Additive effect of mesenchymal stem cells and defibrotide in an arterial rat thrombosis model.

PubMed

Dilli, Dilek; Kılıç, Emine; Yumuşak, Nihat; Beken, Serdar; Uçkan Çetinkaya, Duygu; Karabulut, Ramazan; Zenciroğlu, Ayşegu L

2017-06-01

In this study, we aimed to investigate the additive effect of mesenchymal stem cells (MSC) and defibrotide (DFT) in a rat model of femoral arterial thrombosis. Thirty Sprague Dawley rats were included. An arterial thrombosis model by ferric chloride (FeCl3) was developed in the left femoral artery. The rats were equally assigned to 5 groups: Group 1-Sham-operated (without arterial injury); Group 2-Phosphate buffered saline (PBS) injected; Group 3-MSC; Group 4-DFT; Group 5-MSC + DFT. All had two intraperitoneal injections of 0.5 ml: the 1st injection was 4 h after the procedure and the 2nd one 48 h after the 1st injection. The rats were sacrificed 7 days after the 2nd injection. Although the use of human bone marrow-derived (hBM) hBM-MSC or DFT alone enabled partial resolution of the thrombus, combining them resulted in near-complete resolution. Neovascularization was two-fold better in hBM-MSC + DFT treated rats (11.6 ± 2.4 channels) compared with the hBM-MSC (3.8 ± 2.7 channels) and DFT groups (5.5 ± 1.8 channels) (P < 0.0001 and P= 0.002, respectively). The combined use of hBM-MSC and DFT in a rat model of arterial thrombosis showed additive effect resulting in near-complete resolution of the thrombus.

Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

PubMed

Hong, X; Harris, C J

2000-01-01

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Testing a Gender Additive Model: The Role of Body Image in Adolescent Depression

ERIC Educational Resources Information Center

Bearman, Sarah Kate; Stice, Eric

2008-01-01

Despite consistent evidence that adolescent girls are at greater risk of developing depression than adolescent boys, risk factor models that account for this difference have been elusive. The objective of this research was to examine risk factors proposed by the "gender additive" model of depression that attempts to partially explain the increased…

Shell model for drag reduction with polymer additives in homogeneous turbulence.

PubMed

Benzi, Roberto; De Angelis, Elisabetta; Govindarajan, Rama; Procaccia, Itamar

2003-07-01

Recent direct numerical simulations of the finite-extensibility nonlinear elastic dumbbell model with the Peterlin approximation of non-Newtonian hydrodynamics revealed that the phenomenon of drag reduction by polymer additives exists (albeit in reduced form) also in homogeneous turbulence. We use here a simple shell model for homogeneous viscoelastic flows, which recaptures the essential observations of the full simulations. The simplicity of the shell model allows us to offer a transparent explanation of the main observations. It is shown that the mechanism for drag reduction operates mainly on large scales. Understanding the mechanism allows us to predict how the amount of drag reduction depends on the various parameters in the model. The main conclusion is that drag reduction is not a universal phenomenon; it peaks in a window of parameters such as the Reynolds number and the relaxation rate of the polymer.

Incorporating additional tree and environmental variables in a lodgepole pine stem profile model

Treesearch

John C. Byrne

1993-01-01

A new variable-form segmented stem profile model is developed for lodgepole pine (Pinus contorta) trees from the northern Rocky Mountains of the United States. I improved estimates of stem diameter by predicting two of the model coefficients with linear equations using a measure of tree form, defined as a ratio of dbh and total height. Additional improvements were...

Sidewalk undermining studies : phase III, field and model studies.

DOT National Transportation Integrated Search

1979-01-01

The results of the early studies of the undermining problems are summarized in the initial portion of this report. Additionally, the design and use of a model sidewalk for testing procedures for preventing undermining are described. Based upon tests ...

Spontaneous collective synchronization in the Kuramoto model with additional non-local interactions

NASA Astrophysics Data System (ADS)

Gupta, Shamik

2017-10-01

In the context of the celebrated Kuramoto model of globally-coupled phase oscillators of distributed natural frequencies, which serves as a paradigm to investigate spontaneous collective synchronization in many-body interacting systems, we report on a very rich phase diagram in presence of thermal noise and an additional non-local interaction on a one-dimensional periodic lattice. Remarkably, the phase diagram involves both equilibrium and non-equilibrium phase transitions. In two contrasting limits of the dynamics, we obtain exact analytical results for the phase transitions. These two limits correspond to (i) the absence of thermal noise, when the dynamics reduces to that of a non-linear dynamical system, and (ii) the oscillators having the same natural frequency, when the dynamics becomes that of a statistical system in contact with a heat bath and relaxing to a statistical equilibrium state. In the former case, our exact analysis is based on the use of the so-called Ott-Antonsen ansatz to derive a reduced set of nonlinear partial differential equations for the macroscopic evolution of the system. Our results for the case of statistical equilibrium are on the other hand obtained by extending the well-known transfer matrix approach for nearest-neighbor Ising model to consider non-local interactions. The work offers a case study of exact analysis in many-body interacting systems. The results obtained underline the crucial role of additional non-local interactions in either destroying or enhancing the possibility of observing synchrony in mean-field systems exhibiting spontaneous synchronization.

Parameters and pitfalls to consider in the conduct of food additive research, Carrageenan as a case study.

PubMed

Weiner, Myra L

2016-01-01

This paper provides guidance on the conduct of new in vivo and in vitro studies on high molecular weight food additives, with carrageenan, the widely used food additive, as a case study. It is important to understand the physical/chemical properties and to verify the identity/purity, molecular weight and homogeneity/stability of the additive in the vehicle for oral delivery. The strong binding of CGN to protein in rodent chow or infant formula results in no gastrointestinal tract exposure to free CGN. It is recommended that doses of high Mw non-caloric, non-nutritive additives not exceed 5% by weight of total solid diet to avoid potential nutritional effects. Addition of some high Mw additives at high concentrations to liquid nutritional supplements increases viscosity and may affect palatability, caloric intake and body weight gain. In in vitro studies, the use of well-characterized, relevant cell types and the appropriate composition of the culture media are necessary for proper conduct and interpretation. CGN is bound to media protein and not freely accessible to cells in vitro. Interpretation of new studies on food additives should consider the interaction of food additives with the vehicle components and the appropriateness of the animal or cell model and dose-response. Copyright © 2015 FMC Corporation. Published by Elsevier Ltd.. All rights reserved.

Functional Resilience and Response to a Dietary Additive (Kefir) in Models of Foregut and Hindgut Microbial Fermentation In Vitro

PubMed Central

de la Fuente, Gabriel; Jones, Eleanor; Jones, Shann; Newbold, Charles J.

2017-01-01

Stability in gut ecosystems is an important area of study that impacts on the use of additives and is related with several pathologies. Kefir is a fermented milk drink made with a consortium of yeast and bacteria as a fermentation starter, of which the use as additive in companion and livestock animals has increased in the last few years. To investigate the effect of kefir milk on foregut and hindgut digestive systems, an in vitro approach was followed. Either rumen fluid or horse fecal contents were used as a microbial inoculate and the inclusion of kefir (fresh, autoclaved, or pasteurized) was tested. Gas production over 72 h of incubation was recorded and pH, volatile fatty acids (VFAs), lactate and ammonia concentration as well as lactic acid (LAB) and acetic acid bacteria, and yeast total numbers were also measured. Both direct and indirect (by subtracting their respective blanks) effects were analyzed and a multivariate analysis was performed to compare foregut and hindgut fermentation models. Addition of kefir boosted the fermentation by increasing molar concentration of VFAs and ammonia and shifting the Acetate to Propionate ratio in both models but heat processing techniques like pasteurization or autoclaving influenced the way the kefir is fermented and reacts with the present microbiota. In terms of comparison between both models, the foregut model seems to be less affected by the inclusion of Kefir than the hindgut model. In terms of variability in the response, the hindgut model appeared to be more variable than the foregut model in the way that it reacted indirectly to the addition of different types of kefir. PMID:28702019

Functional Resilience and Response to a Dietary Additive (Kefir) in Models of Foregut and Hindgut Microbial Fermentation In Vitro.

PubMed

de la Fuente, Gabriel; Jones, Eleanor; Jones, Shann; Newbold, Charles J

2017-01-01

Stability in gut ecosystems is an important area of study that impacts on the use of additives and is related with several pathologies. Kefir is a fermented milk drink made with a consortium of yeast and bacteria as a fermentation starter, of which the use as additive in companion and livestock animals has increased in the last few years. To investigate the effect of kefir milk on foregut and hindgut digestive systems, an in vitro approach was followed. Either rumen fluid or horse fecal contents were used as a microbial inoculate and the inclusion of kefir (fresh, autoclaved, or pasteurized) was tested. Gas production over 72 h of incubation was recorded and pH, volatile fatty acids (VFAs), lactate and ammonia concentration as well as lactic acid (LAB) and acetic acid bacteria, and yeast total numbers were also measured. Both direct and indirect (by subtracting their respective blanks) effects were analyzed and a multivariate analysis was performed to compare foregut and hindgut fermentation models. Addition of kefir boosted the fermentation by increasing molar concentration of VFAs and ammonia and shifting the Acetate to Propionate ratio in both models but heat processing techniques like pasteurization or autoclaving influenced the way the kefir is fermented and reacts with the present microbiota. In terms of comparison between both models, the foregut model seems to be less affected by the inclusion of Kefir than the hindgut model. In terms of variability in the response, the hindgut model appeared to be more variable than the foregut model in the way that it reacted indirectly to the addition of different types of kefir.

A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

NASA Astrophysics Data System (ADS)

Lian, Yanping; Lin, Stephen; Yan, Wentao; Liu, Wing Kam; Wagner, Gregory J.

2018-05-01

In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

NASA Astrophysics Data System (ADS)

Lian, Yanping; Lin, Stephen; Yan, Wentao; Liu, Wing Kam; Wagner, Gregory J.

2018-01-01

In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

Strengthen forensic entomology in court--the need for data exploration and the validation of a generalised additive mixed model.

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.

Modelling the average velocity of propagation of the flame front in a gasoline engine with hydrogen additives

NASA Astrophysics Data System (ADS)

Smolenskaya, N. M.; Smolenskii, V. V.

2018-01-01

The paper presents models for calculating the average velocity of propagation of the flame front, obtained from the results of experimental studies. Experimental studies were carried out on a single-cylinder gasoline engine UIT-85 with hydrogen additives up to 6% of the mass of fuel. The article shows the influence of hydrogen addition on the average velocity propagation of the flame front in the main combustion phase. The dependences of the turbulent propagation velocity of the flame front in the second combustion phase on the composition of the mixture and operating modes. The article shows the influence of the normal combustion rate on the average flame propagation velocity in the third combustion phase.

Model Scramjet Inlet Unstart Induced by Mass Addition and Heat Release

NASA Astrophysics Data System (ADS)

Im, Seong-Kyun; Baccarella, Damiano; McGann, Brendan; Liu, Qili; Wermer, Lydiy; Do, Hyungrok

2015-11-01

The inlet unstart phenomena in a model scramjet are investigated at an arc-heated hypersonic wind tunnel. The unstart induced by nitrogen or ethylene jets at low or high enthalpy Mach 4.5 freestream flow conditions are compared. The jet injection pressurizes the downstream flow by mass addition and flow blockage. In case of the ethylene jet injection, heat release from combustion increases the backpressure further. Time-resolved schlieren imaging is performed at the jet and the lip of the model inlet to visualize the flow features during unstart. High frequency pressure measurements are used to provide information on pressure fluctuation at the scramjet wall. In both of the mass and heat release driven unstart cases, it is observed that there are similar flow transient and quasi-steady behaviors of unstart shockwave system during the unstart processes. Combustion driven unstart induces severe oscillatory flow motions of the jet and the unstart shock at the lip of the scramjet inlet after the completion of the unstart process, while the unstarted flow induced by solely mass addition remains relatively steady. The discrepancies between the processes of mass and heat release driven unstart are explained by flow choking mechanism.

Diagnostic utility of appetite loss in addition to existing prediction models for community-acquired pneumonia in the elderly: a prospective diagnostic study in acute care hospitals in Japan.

PubMed

Takada, Toshihiko; Yamamoto, Yosuke; Terada, Kazuhiko; Ohta, Mitsuyasu; Mikami, Wakako; Yokota, Hajime; Hayashi, Michio; Miyashita, Jun; Azuma, Teruhisa; Fukuma, Shingo; Fukuhara, Shunichi

2017-11-08

Diagnosis of community-acquired pneumonia (CAP) in the elderly is often delayed because of atypical presentation and non-specific symptoms, such as appetite loss, falls and disturbance in consciousness. The aim of this study was to investigate the external validity of existing prediction models and the added value of the non-specific symptoms for the diagnosis of CAP in elderly patients. Prospective cohort study. General medicine departments of three teaching hospitals in Japan. A total of 109 elderly patients who consulted for upper respiratory symptoms between 1 October 2014 and 30 September 2016. The reference standard for CAP was chest radiograph evaluated by two certified radiologists. The existing models were externally validated for diagnostic performance by calibration plot and discrimination. To evaluate the additional value of the non-specific symptoms to the existing prediction models, we developed an extended logistic regression model. Calibration, discrimination, category-free net reclassification improvement (NRI) and decision curve analysis (DCA) were investigated in the extended model. Among the existing models, the model by van Vugt demonstrated the best performance, with an area under the curve of 0.75(95% CI 0.63 to 0.88); calibration plot showed good fit despite a significant Hosmer-Lemeshow test (p=0.017). Among the non-specific symptoms, appetite loss had positive likelihood ratio of 3.2 (2.0-5.3), negative likelihood ratio of 0.4 (0.2-0.7) and OR of 7.7 (3.0-19.7). Addition of appetite loss to the model by van Vugt led to improved calibration at p=0.48, NRI of 0.53 (p=0.019) and higher net benefit by DCA. Information on appetite loss improved the performance of an existing model for the diagnosis of CAP in the elderly. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

In-Situ monitoring and modeling of metal additive manufacturing powder bed fusion

NASA Astrophysics Data System (ADS)

Alldredge, Jacob; Slotwinski, John; Storck, Steven; Kim, Sam; Goldberg, Arnold; Montalbano, Timothy

2018-04-01

One of the major challenges in metal additive manufacturing is developing in-situ sensing and feedback control capabilities to eliminate build errors and allow qualified part creation without the need for costly and destructive external testing. Previously, many groups have focused on high fidelity numerical modeling and true temperature thermal imaging systems. These approaches require large computational resources or costly hardware that requires complex calibration and are difficult to integrate into commercial systems. In addition, due to the rapid change in the state of the material as well as its surface properties, getting true temperature is complicated and difficult. Here, we describe a different approach where we implement a low cost thermal imaging solution allowing for relative temperature measurements sufficient for detecting unwanted process variability. We match this with a faster than real time qualitative model that allows the process to be rapidly modeled during the build. The hope is to combine these two, allowing for the detection of anomalies in real time, enabling corrective action to potentially be taken, or parts to be stopped immediately after the error, saving material and time. Here we describe our sensor setup, its costs and abilities. We also show the ability to detect in real time unwanted process deviations. We also show that the output of our high speed model agrees qualitatively with experimental results. These results lay the groundwork for our vision of an integrated feedback and control scheme that combines low cost, easy to use sensors and fast modeling for process deviation monitoring.

Does the high–tech industry consistently reduce CO{sub 2} emissions? Results from nonparametric additive regression model

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

Xu, Bin; Research Center of Applied Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013; Lin, Boqiang, E-mail: bqlin@xmu.edu.cn

China is currently the world's largest carbon dioxide (CO{sub 2}) emitter. Moreover, total energy consumption and CO{sub 2} emissions in China will continue to increase due to the rapid growth of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO{sub 2} emissions at the moment or in the future. However, ignoring the existing nonlinear links between economic variables, most scholars use traditional linear models to explore the impact of the high–tech industry on CO{sub 2} emissions from an aggregate perspective. Few studies have focused on nonlinear relationships and regional differences in China. Basedmore » on panel data of 1998–2014, this study uses the nonparametric additive regression model to explore the nonlinear effect of the high–tech industry from a regional perspective. The estimated results show that the residual sum of squares (SSR) of the nonparametric additive regression model in the eastern, central and western regions are 0.693, 0.054 and 0.085 respectively, which are much less those that of the traditional linear regression model (3.158, 4.227 and 7.196). This verifies that the nonparametric additive regression model has a better fitting effect. Specifically, the high–tech industry produces an inverted “U–shaped” nonlinear impact on CO{sub 2} emissions in the eastern region, but a positive “U–shaped” nonlinear effect in the central and western regions. Therefore, the nonlinear impact of the high–tech industry on CO{sub 2} emissions in the three regions should be given adequate attention in developing effective abatement policies. - Highlights: • The nonlinear effect of the high–tech industry on CO{sub 2} emissions was investigated. • The high–tech industry yields an inverted “U–shaped” effect in the eastern region. • The high–tech industry has a positive “U–shaped” nonlinear effect in other regions. • The linear

“Skill of Generalized Additive Model to Detect PM2.5 Health ...

EPA Pesticide Factsheets

Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and by implication scales and periods that are not shared). Hospital admissions, meteorology (temperature and relative humidity), and air quality (PM2.5 and daily maximum ozone) for New York City during the period 2000-2006 were decomposed into temporal scales ranging from 2 days to greater than two years using a complex wavelet transform. Health effects were modeled as functions of the wavelet components of meteorology and air quality using the generalized additive model (GAM) framework. This simulation study showed that GAM is extremely successful at extracting and estimating a health effect embedded in a dataset. It also shows that, if the objective in mind is to estimate the health signal but not to fully explain this signal, a simple GAM model with a single confounder (calendar time) whose smooth representation includes a sufficient number of constraints is as good as a more complex model.Introduction. In the context of wavelet regression, confounding occurs when two or more independent variables interact with the dependent variable at the same frequency. Confounding also acts on a variety of time scales, changing the PM2.5 coefficient (magnitude and sign) and its significance ac

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China.

PubMed

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China

PubMed Central

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia. PMID:27002822

Nonlinear feedback in a six-dimensional Lorenz Model: impact of an additional heating term

NASA Astrophysics Data System (ADS)

Shen, B.-W.

2015-03-01

In this study, a six-dimensional Lorenz model (6DLM) is derived, based on a recent study using a five-dimensional (5-D) Lorenz model (LM), in order to examine the impact of an additional mode and its accompanying heating term on solution stability. The new mode added to improve the representation of the steamfunction is referred to as a secondary streamfunction mode, while the two additional modes, that appear in both the 6DLM and 5DLM but not in the original LM, are referred to as secondary temperature modes. Two energy conservation relationships of the 6DLM are first derived in the dissipationless limit. The impact of three additional modes on solution stability is examined by comparing numerical solutions and ensemble Lyapunov exponents of the 6DLM and 5DLM as well as the original LM. For the onset of chaos, the critical value of the normalized Rayleigh number (rc) is determined to be 41.1. The critical value is larger than that in the 3DLM (rc ~ 24.74), but slightly smaller than the one in the 5DLM (rc ~ 42.9). A stability analysis and numerical experiments obtained using generalized LMs, with or without simplifications, suggest the following: (1) negative nonlinear feedback in association with the secondary temperature modes, as first identified using the 5DLM, plays a dominant role in providing feedback for improving the solution's stability of the 6DLM, (2) the additional heating term in association with the secondary streamfunction mode may destabilize the solution, and (3) overall feedback due to the secondary streamfunction mode is much smaller than the feedback due to the secondary temperature modes; therefore, the critical Rayleigh number of the 6DLM is comparable to that of the 5DLM. The 5DLM and 6DLM collectively suggest different roles for small-scale processes (i.e., stabilization vs. destabilization), consistent with the following statement by Lorenz (1972): If the flap of a butterfly's wings can be instrumental in generating a tornado, it can

Nonlinear feedback in a six-dimensional Lorenz model: impact of an additional heating term

NASA Astrophysics Data System (ADS)

Shen, B.-W.

2015-12-01

In this study, a six-dimensional Lorenz model (6DLM) is derived, based on a recent study using a five-dimensional (5-D) Lorenz model (LM), in order to examine the impact of an additional mode and its accompanying heating term on solution stability. The new mode added to improve the representation of the streamfunction is referred to as a secondary streamfunction mode, while the two additional modes, which appear in both the 6DLM and 5DLM but not in the original LM, are referred to as secondary temperature modes. Two energy conservation relationships of the 6DLM are first derived in the dissipationless limit. The impact of three additional modes on solution stability is examined by comparing numerical solutions and ensemble Lyapunov exponents of the 6DLM and 5DLM as well as the original LM. For the onset of chaos, the critical value of the normalized Rayleigh number (rc) is determined to be 41.1. The critical value is larger than that in the 3DLM (rc ~ 24.74), but slightly smaller than the one in the 5DLM (rc ~ 42.9). A stability analysis and numerical experiments obtained using generalized LMs, with or without simplifications, suggest the following: (1) negative nonlinear feedback in association with the secondary temperature modes, as first identified using the 5DLM, plays a dominant role in providing feedback for improving the solution's stability of the 6DLM, (2) the additional heating term in association with the secondary streamfunction mode may destabilize the solution, and (3) overall feedback due to the secondary streamfunction mode is much smaller than the feedback due to the secondary temperature modes; therefore, the critical Rayleigh number of the 6DLM is comparable to that of the 5DLM. The 5DLM and 6DLM collectively suggest different roles for small-scale processes (i.e., stabilization vs. destabilization), consistent with the following statement by Lorenz (1972): "If the flap of a butterfly's wings can be instrumental in generating a tornado, it can

A study on the applications of AI in finishing of additive manufacturing parts

NASA Astrophysics Data System (ADS)

Fathima Patham, K.

2017-06-01

Artificial intelligent and computer simulation are the technological powerful tools for solving complex problems in the manufacturing industries. Additive Manufacturing is one of the powerful manufacturing techniques that provide design flexibilities to the products. The products with complex shapes are directly manufactured without the need of any machining and tooling using Additive Manufacturing. However, the main drawback of the components produced using the Additive Manufacturing processes is the quality of the surfaces. This study aims to minimize the defects caused during Additive Manufacturing with the aid of Artificial Intelligence. The developed AI system has three layers, each layer is trying to eliminate or minimize the production errors. The first layer of the AI system optimizes the digitization of the 3D CAD model of the product and hence reduces the stair case errors. The second layer of the AI system optimizes the 3D printing machine parameters in order to eliminate the warping effect. The third layer of AI system helps to choose the surface finishing technique suitable for the printed component based on the Degree of Complexity of the product and the material. The efficiency of the developed AI system was examined on the functional parts such as gears.

Anatomically ordered tapping interferes more with one-digit addition than two-digit addition: a dual-task fMRI study.

PubMed

Soylu, Firat; Newman, Sharlene D

2016-02-01

Fingers are used as canonical representations for numbers across cultures. In previous imaging studies, it was shown that arithmetic processing activates neural resources that are known to participate in finger movements. Additionally, in one dual-task study, it was shown that anatomically ordered finger tapping disrupts addition and subtraction more than multiplication, possibly due to a long-lasting effect of early finger counting experiences on the neural correlates and organization of addition and subtraction processes. How arithmetic task difficulty and tapping complexity affect the concurrent performance is still unclear. If early finger counting experiences have bearing on the neural correlates of arithmetic in adults, then one would expect anatomically and non-anatomically ordered tapping to have different interference effects, given that finger counting is usually anatomically ordered. To unravel these issues, we studied how (1) arithmetic task difficulty and (2) the complexity of the finger tapping sequence (anatomical vs. non-anatomical ordering) affect concurrent performance and use of key neural circuits using a mixed block/event-related dual-task fMRI design with adult participants. The results suggest that complexity of the tapping sequence modulates interference on addition, and that one-digit addition (fact retrieval), compared to two-digit addition (calculation), is more affected from anatomically ordered tapping. The region-of-interest analysis showed higher left angular gyrus BOLD response for one-digit compared to two-digit addition, and in no-tapping conditions than dual tapping conditions. The results support a specific association between addition fact retrieval and anatomically ordered finger movements in adults, possibly due to finger counting strategies that deploy anatomically ordered finger movements early in the development.

Kinetic studies of retinol addition radicals.

PubMed

El-Agamey, Ali; Fukuzumi, Shunichi; Naqvi, K Razi; McGarvey, David J

2011-03-07

Retinol neutral radicals (RS-retinol˙), generated from the reaction of retinol with 4-pyridylthiyl and 2-pyridylthiyl radicals in argon-saturated methanol, undergo β-elimination, which can be monitored via the slow secondary absorption rise at 380 nm attributed to the rearrangement of the unstable retinol neutral addition radicals to the more stable addition radicals. Rate constants for the β-elimination reactions (k(β)) of 4-PyrS-retinol˙ were measured at different temperatures and the Arrhenius equation for the reaction is described by log (k(β)/s(-1)) = (12.7 ± 0.2) - (54.3 ± 1.3)/θ, where θ = 2.3RT kJ mol(-1). The reactivities of retinol addition radicals (RS-retinol˙), generated from the reaction of retinol with various thiyl radicals, towards oxygen have also been investigated in methanol. In the presence of oxygen, the decay of RS-retinol˙ fits to biexponential kinetics and both observed rate constants for the RS-retinol˙ decay are oxygen-concentration dependent. This suggests that at least two thiyl addition radicals, formed from the reaction of RS˙ with retinol, undergo oxygen addition reactions. In light of the estimated rate constants for oxygen addition to RS-retinol˙ and RS-CAR˙ (CAR: carotenoid), the antioxidant-prooxidant properties of retinol are discussed.

Amino-Acid Network Clique Analysis of Protein Mutation Non-Additive Effects: A Case Study of Lysozme.

PubMed

Ming, Dengming; Chen, Rui; Huang, He

2018-05-10

Optimizing amino-acid mutations in enzyme design has been a very challenging task in modern bio-industrial applications. It is well known that many successful designs often hinge on extensive correlations among mutations at different sites within the enzyme, however, the underpinning mechanism for these correlations is far from clear. Here, we present a topology-based model to quantitively characterize non-additive effects between mutations. The method is based on the molecular dynamic simulations and the amino-acid network clique analysis. It examines if the two mutation sites of a double-site mutation fall into to a 3-clique structure, and associates such topological property of mutational site spatial distribution with mutation additivity features. We analyzed 13 dual mutations of T4 phage lysozyme and found that the clique-based model successfully distinguishes highly correlated or non-additive double-site mutations from those additive ones whose component mutations have less correlation. We also applied the model to protein Eglin c whose structural topology is significantly different from that of T4 phage lysozyme, and found that the model can, to some extension, still identify non-additive mutations from additive ones. Our calculations showed that mutation non-additive effects may heavily depend on a structural topology relationship between mutation sites, which can be quantitatively determined using amino-acid network k -cliques. We also showed that double-site mutation correlations can be significantly altered by exerting a third mutation, indicating that more detailed physicochemical interactions should be considered along with the network clique-based model for better understanding of this elusive mutation-correlation principle.

Boosted structured additive regression for Escherichia coli fed-batch fermentation modeling.

PubMed

Melcher, Michael; Scharl, Theresa; Luchner, Markus; Striedner, Gerald; Leisch, Friedrich

2017-02-01

The quality of biopharmaceuticals and patients' safety are of highest priority and there are tremendous efforts to replace empirical production process designs by knowledge-based approaches. Main challenge in this context is that real-time access to process variables related to product quality and quantity is severely limited. To date comprehensive on- and offline monitoring platforms are used to generate process data sets that allow for development of mechanistic and/or data driven models for real-time prediction of these important quantities. Ultimate goal is to implement model based feed-back control loops that facilitate online control of product quality. In this contribution, we explore structured additive regression (STAR) models in combination with boosting as a variable selection tool for modeling the cell dry mass, product concentration, and optical density on the basis of online available process variables and two-dimensional fluorescence spectroscopic data. STAR models are powerful extensions of linear models allowing for inclusion of smooth effects or interactions between predictors. Boosting constructs the final model in a stepwise manner and provides a variable importance measure via predictor selection frequencies. Our results show that the cell dry mass can be modeled with a relative error of about ±3%, the optical density with ±6%, the soluble protein with ±16%, and the insoluble product with an accuracy of ±12%. Biotechnol. Bioeng. 2017;114: 321-334. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Assessing the effect, on animal model, of mixture of food additives, on the water balance.

PubMed

Friedrich, Mariola; Kuchlewska, Magdalena

2013-01-01

The purpose of this study was to determine, on the animal model, the effect of modification of diet composition and administration of selected food additives on water balance in the body. The study was conducted with 48 males and 48 females (separately for each sex) of Wistar strain rats divided into four groups. For drinking, the animals from groups I and III were receiving water, whereas the animals from groups II and IV were administered 5 ml of a solution of selected food additives (potassium nitrate - E 252, sodium nitrite - E 250, benzoic acid - E 210, sorbic acid - E 200, and monosodium glutamate - E 621). Doses of the administered food additives were computed taking into account the average intake by men, expressed per body mass unit. Having drunk the solution, the animals were provided water for drinking. The mixture of selected food additives applied in the experiment was found to facilitate water retention in the body both in the case of both male and female rats, and differences observed between the volume of ingested fluids and the volume of excreted urine were statistically significant in the animals fed the basal diet. The type of feed mixture provided to the animals affected the site of water retention - in the case of animals receiving the basal diet analyses demonstrated a significant increase in water content in the liver tissue, whereas in the animals fed the modified diet water was observed to accumulate in the vascular bed. Taking into account the fact of water retention in the vascular bed, the effects of food additives intake may be more adverse in the case of females.

S-SIMS and MetA-SIMS study of organic additives in thin polymer coatings

NASA Astrophysics Data System (ADS)

Adriaensen, L.; Vangaever, F.; Lenaerts, J.; Gijbels, R.

2006-07-01

In the present study a methodology for TOF-S-SIMS measurements is developed to gain information on the distribution of molecules on and in polymer coatings (thickness ˜100 μm). Experiments were carried out on model systems consisting of one or more additive-containing polyvinylbutyral coatings. Several organic additives were selected: carbocyanine dyes, basonyl blue and the pharmaceutical risperidone. The additives have been measured as pure compounds on a Si substrate to obtain good reference spectra. After optimisation of the sample preparation method, the coatings were embedded in epoxy resin and stored in an oven (60 °C) for 24 h. Cross-sections were made by means of a microtome. S-SIMS spectra were taken on the prepared cross-sections before and after Au was deposited on the sample surface. Compared to the untreated samples, the Au covered samples give rise to more intense secondary ion signals. Generally, signals of the intact cations were more intense than those of the fragment ions. Apart from mass spectra, images of the additive distribution in the coatings could also be acquired by recording structural ion signals. It was possible to make secondary ion images of the additive molecule ions with a (sub)-micrometer lateral resolution.

Estimating gestational age at birth from fundal height and additional anthropometrics: a prospective cohort study.

PubMed

Pugh, S J; Ortega-Villa, A M; Grobman, W; Newman, R B; Owen, J; Wing, D A; Albert, P S; Grantz, K L

2018-02-23

Accurate assessment of gestational age (GA) is critical to paediatric care, but is limited in developing countries without access to ultrasound. Our objectives were to assess the accuracy of prediction of GA at birth and preterm birth classification using routinely collected anthropometry measures. Prospective cohort study. United States. A total of 2334 non-obese and 468 obese pregnant women. Enrolment GA was determined based on last menstrual period, confirmed by first-trimester ultrasound. Maternal anthropometry and fundal height (FH) were measured by a standardised protocol at study visits; FH alone was additionally abstracted from medical charts. Neonatal anthropometry measurements were obtained at birth. To estimate GA at delivery, we developed three predictor models using longitudinal FH alone and with maternal and neonatal anthropometry. For all predictors, we repeatedly sampled observations to construct training (60%) and test (40%) sets. Linear mixed models incorporated longitudinal maternal anthropometry and a shared parameter model incorporated neonatal anthropometry. We assessed models' accuracy under varied scenarios. Estimated GA at delivery. Prediction error for various combinations of anthropometric measures ranged between 13.9 and 14.9 days. Longitudinal FH alone predicted GA within 14.9 days with relatively stable prediction errors across individual race/ethnicities [whites (13.9 days), blacks (15.1 days), Hispanics (15.5 days) and Asians (13.1 days)], and correctly identified 75% of preterm births. The model was robust to additional scenarios. In low-risk, non-obese women, longitudinal FH measures alone can provide a reasonably accurate assessment of GA when ultrasound measures are not available. Longitudinal fundal height alone predicts gestational age at birth when ultrasound measures are unavailable. © 2018 Royal College of Obstetricians and Gynaecologists.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series.

PubMed

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

NASA Astrophysics Data System (ADS)

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

Quasi-additive estimates on the Hamiltonian for the one-dimensional long range Ising model

NASA Astrophysics Data System (ADS)

Littin, Jorge; Picco, Pierre

2017-07-01

In this work, we study the problem of getting quasi-additive bounds for the Hamiltonian of the long range Ising model, when the two-body interaction term decays proportionally to 1/d2 -α , α ∈(0,1 ) . We revisit the paper by Cassandro et al. [J. Math. Phys. 46, 053305 (2005)] where they extend to the case α ∈[0 ,ln3/ln2 -1 ) the result of the existence of a phase transition by using a Peierls argument given by Fröhlich and Spencer [Commun. Math. Phys. 84, 87-101 (1982)] for α =0 . The main arguments of Cassandro et al. [J. Math. Phys. 46, 053305 (2005)] are based in a quasi-additive decomposition of the Hamiltonian in terms of hierarchical structures called triangles and contours, which are related to the original definition of contours introduced by Fröhlich and Spencer [Commun. Math. Phys. 84, 87-101 (1982)]. In this work, we study the existence of a quasi-additive decomposition of the Hamiltonian in terms of the contours defined in the work of Cassandro et al. [J. Math. Phys. 46, 053305 (2005)]. The most relevant result obtained is Theorem 4.3 where we show that there is a quasi-additive decomposition for the Hamiltonian in terms of contours when α ∈[0,1 ) but not in terms of triangles. The fact that it cannot be a quasi-additive bound in terms of triangles lead to a very interesting maximization problem whose maximizer is related to a discrete Cantor set. As a consequence of the quasi-additive bounds, we prove that we can generalise the [Cassandro et al., J. Math. Phys. 46, 053305 (2005)] result, that is, a Peierls argument, to the whole interval α ∈[0,1 ) . We also state here the result of Cassandro et al. [Commun. Math. Phys. 327, 951-991 (2014)] about cluster expansions which implies that Theorem 2.4 that concerns interfaces and Theorem 2.5 that concerns n point truncated correlation functions in Cassandro et al. [Commun. Math. Phys. 327, 951-991 (2014)] are valid for all α ∈[0,1 ) instead of only α ∈[0 ,ln3/ln2 -1 ) .

Enlarged leukocyte referent libraries can explain additional variance in blood-based epigenome-wide association studies.

PubMed

Kim, Stephanie; Eliot, Melissa; Koestler, Devin C; Houseman, Eugene A; Wetmur, James G; Wiencke, John K; Kelsey, Karl T

2016-09-01

We examined whether variation in blood-based epigenome-wide association studies could be more completely explained by augmenting existing reference DNA methylation libraries. We compared existing and enhanced libraries in predicting variability in three publicly available 450K methylation datasets that collected whole-blood samples. Models were fit separately to each CpG site and used to estimate the additional variability when adjustments for cell composition were made with each library. Calculation of the mean difference in the CpG-specific residual sums of squares error between models for an arthritis, aging and metabolic syndrome dataset, indicated that an enhanced library explained significantly more variation across all three datasets (p < 10(-3)). Pathologically important immune cell subtypes can explain important variability in epigenome-wide association studies done in blood.

Inaccuracies in additive manufactured medical skull models caused by the DICOM to STL conversion process.

PubMed

Huotilainen, Eero; Jaanimets, Risto; Valášek, Jiří; Marcián, Petr; Salmi, Mika; Tuomi, Jukka; Mäkitie, Antti; Wolff, Jan

2014-07-01

The process of fabricating physical medical skull models requires many steps, each of which is a potential source of geometric error. The aim of this study was to demonstrate inaccuracies and differences caused by DICOM to STL conversion in additively manufactured medical skull models. Three different institutes were requested to perform an automatic reconstruction from an identical DICOM data set of a patients undergoing tumour surgery into an STL file format using their software of preference. The acquired digitized STL data sets were assessed and compared and subsequently used to fabricate physical medical skull models. The three fabricated skull models were then scanned, and differences in the model geometries were assessed using established CAD inspection software methods. A large variation was noted in size and anatomical geometries of the three physical skull models fabricated from an identical (or "a single") DICOM data set. A medical skull model of the same individual can vary markedly depending on the DICOM to STL conversion software and the technical parameters used. Clinicians should be aware of this inaccuracy in certain applications. Copyright © 2013 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

78 FR 12271 - Wireline Competition Bureau Seeks Additional Comment In Connect America Cost Model Virtual Workshop

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-22

... Competition Bureau seeks public input on additional questions relating to modeling voice capability and Annual... submitting comments and additional information on the rulemaking process, see the SUPPLEMENTARY INFORMATION section of this document. FOR FURTHER INFORMATION CONTACT: Katie King, Wireline Competition Bureau at (202...

Addition Table of Colours: Additive and Subtractive Mixtures Described Using a Single Reasoning Model

ERIC Educational Resources Information Center

Mota, A. R.; Lopes dos Santos, J. M. B.

2014-01-01

Students' misconceptions concerning colour phenomena and the apparent complexity of the underlying concepts--due to the different domains of knowledge involved--make its teaching very difficult. We have developed and tested a teaching device, the addition table of colours (ATC), that encompasses additive and subtractive mixtures in a single…

Septic tank additive impacts on microbial populations.

PubMed

Pradhan, S; Hoover, M T; Clark, G H; Gumpertz, M; Wollum, A G; Cobb, C; Strock, J

2008-01-01

Environmental health specialists, other onsite wastewater professionals, scientists, and homeowners have questioned the effectiveness of septic tank additives. This paper describes an independent, third-party, field scale, research study of the effects of three liquid bacterial septic tank additives and a control (no additive) on septic tank microbial populations. Microbial populations were measured quarterly in a field study for 12 months in 48 full-size, functioning septic tanks. Bacterial populations in the 48 septic tanks were statistically analyzed with a mixed linear model. Additive effects were assessed for three septic tank maintenance levels (low, intermediate, and high). Dunnett's t-test for tank bacteria (alpha = .05) indicated that none of the treatments were significantly different, overall, from the control at the statistical level tested. In addition, the additives had no significant effects on septic tank bacterial populations at any of the septic tank maintenance levels. Additional controlled, field-based research iswarranted, however, to address additional additives and experimental conditions.

Study of mandible reconstruction using a fibula flap with application of additive manufacturing technology.

PubMed

Tsai, Ming-June; Wu, Ching-Tsai

2014-05-06

This study aimed to establish surgical guiding techniques for completing mandible lesion resection and reconstruction of the mandible defect area with fibula sections in one surgery by applying additive manufacturing technology, which can reduce the surgical duration and enhance the surgical accuracy and success rate. A computer assisted mandible reconstruction planning (CAMRP) program was used to calculate the optimal cutting length and number of fibula pieces and design the fixtures for mandible cutting, registration, and arrangement of the fibula segments. The mandible cutting and registering fixtures were then generated using an additive manufacturing system. The CAMRP calculated the optimal fibula cutting length and number of segments based on the location and length of the defective portion of the mandible. The mandible cutting jig was generated according to the boundary surface of the lesion resection on the mandible STL model. The fibular cutting fixture was based on the length of each segment, and the registered fixture was used to quickly arrange the fibula pieces into the shape of the defect area. In this study, the mandibular lesion was reconstructed using registered fibular sections in one step, and the method is very easy to perform. The application of additive manufacturing technology provided customized models and the cutting fixtures and registered fixtures, which can improve the efficiency of clinical application. This study showed that the cutting fixture helped to rapidly complete lesion resection and fibula cutting, and the registered fixture enabled arrangement of the fibula pieces and allowed completion of the mandible reconstruction in a timely manner. Our method can overcome the disadvantages of traditional surgery, which requires a long and different course of treatment and is liable to cause error. With the help of optimal cutting planning by the CAMRP and the 3D printed mandible resection jig and fibula cutting fixture, this all

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

CO2 enrichment and N addition increase nutrient loss from decomposing leaf litter in subtropical model forest ecosystems

PubMed Central

Liu, Juxiu; Fang, Xiong; Deng, Qi; Han, Tianfeng; Huang, Wenjuan; Li, Yiyong

2015-01-01

As atmospheric CO2 concentration increases, many experiments have been carried out to study effects of CO2 enrichment on litter decomposition and nutrient release. However, the result is still uncertain. Meanwhile, the impact of CO2 enrichment on nutrients other than N and P are far less studied. Using open-top chambers, we examined effects of elevated CO2 and N addition on leaf litter decomposition and nutrient release in subtropical model forest ecosystems. We found that both elevated CO2 and N addition increased nutrient (C, N, P, K, Ca, Mg and Zn) loss from the decomposing litter. The N, P, Ca and Zn loss was more than tripled in the chambers exposed to both elevated CO2 and N addition than those in the control chambers after 21 months of treatment. The stimulation of nutrient loss under elevated CO2 was associated with the increased soil moisture, the higher leaf litter quality and the greater soil acidity. Accelerated nutrient release under N addition was related to the higher leaf litter quality, the increased soil microbial biomass and the greater soil acidity. Our results imply that elevated CO2 and N addition will increase nutrient cycling in subtropical China under the future global change. PMID:25608664

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...

Effect of Various Food Additives on the Levels of 4(5)-Methylimidazole in a Soy Sauce Model System.

PubMed

Lee, Sumin; Lee, Jung-Bin; Hwang, Junho; Lee, Kwang-Geun

2016-01-01

In this study, the effect of food additives such as iron sulfate, magnesium sulfate, zinc sulfate, citric acid, gallic acid, and ascorbic acid on the reduction of 4(5)-methylimidazole (4(5)-MI) was investigated using a soy sauce model system. The concentration of 4(5)-MI in the soy sauce model system with 5% (v/v) caramel colorant III was 1404.13 μg/L. The reduction rate of 4(5)-MI level with the addition of 0.1M additives followed in order: iron sulfate (81%) > zinc sulfate (61%) > citric acid (40%) > gallic acid (38%) > ascorbic acid (24%) > magnesium sulfate (13%). Correlations between 4(5)-MI levels and the physicochemical properties of soy sauce, including the amount of caramel colorant, pH value, and color differences, were determined. The highest correlations were found between 4(5)-MI levels and the amount of caramel colorant and pH values (r(2) = 0.9712, r(2) = 0.9378). The concentration of caramel colorants in 8 commercial soy sauces were estimated, and ranged from 0.01 to 1.34% (v/v). © 2015 Institute of Food Technologists®

Relearning To Teach Arithmetic Addition and Subtraction: A Teacher's Study Guide.

ERIC Educational Resources Information Center

Russell, Susan Jo

This package features videotapes and a study guide that are designed to help teachers revisit the operations of addition and subtraction and consider how students can develop meaningful approaches to these operations. The study guides' sessions are on addition, subtraction, the teacher's role, and goals for students and teachers. The readings in…

Enhancement of colour stability of anthocyanins in model beverages by gum arabic addition.

PubMed

Chung, Cheryl; Rojanasasithara, Thananunt; Mutilangi, William; McClements, David Julian

2016-06-15

This study investigated the potential of gum arabic to improve the stability of anthocyanins that are used in commercial beverages as natural colourants. The degradation of purple carrot anthocyanin in model beverage systems (pH 3.0) containing L-ascorbic acid proceeded with a first-order reaction rate during storage (40 °C for 5 days in light). The addition of gum arabic (0.05-5.0%) significantly enhanced the colour stability of anthocyanin, with the most stable systems observed at intermediate levels (1.5%). A further increase in concentration (>1.5%) reduced its efficacy due to a change in the conformation of the gum arabic molecules that hindered their exposure to the anthocyanins. Fluorescence quenching measurements showed that the anthocyanin could have interacted with the glycoprotein fractions of the gum arabic through hydrogen bonding, resulting in enhanced stability. Overall, this study provides valuable information about enhancing the stability of anthocyanins in beverage systems using natural ingredients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structured functional additive regression in reproducing kernel Hilbert spaces.

PubMed

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2014-06-01

Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application.

Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model.

PubMed

Dropkin, Greg

2016-11-24

Analyses of cancer mortality and incidence in Japanese A-bomb survivors have been used to estimate radiation risks, which are generally higher for women. Relative Risk (RR) is usually modelled as a linear function of dose. Extrapolation from data including high doses predicts small risks at low doses. Generalized Additive Models (GAMs) are flexible methods for modelling non-linear behaviour. GAMs are applied to cancer incidence in female low dose subcohorts, using anonymous public data for the 1958 - 1998 Life Span Study, to test for linearity, explore interactions, adjust for the skewed dose distribution, examine significance below 100 mGy, and estimate risks at 10 mGy. For all solid cancer incidence, RR estimated from 0 - 100 mGy and 0 - 20 mGy subcohorts is significantly raised. The response tapers above 150 mGy. At low doses, RR increases with age-at-exposure and decreases with time-since-exposure, the preferred covariate. Using the empirical cumulative distribution of dose improves model fit, and capacity to detect non-linear responses. RR is elevated over wide ranges of covariate values. Results are stable under simulation, or when removing exceptional data cells, or adjusting neutron RBE. Estimates of Excess RR at 10 mGy using the cumulative dose distribution are 10 - 45 times higher than extrapolations from a linear model fitted to the full cohort. Below 100 mGy, quasipoisson models find significant effects for all solid, squamous, uterus, corpus, and thyroid cancers, and for respiratory cancers when age-at-exposure > 35 yrs. Results for the thyroid are compatible with studies of children treated for tinea capitis, and Chernobyl survivors. Results for the uterus are compatible with studies of UK nuclear workers and the Techa River cohort. Non-linear models find large, significant cancer risks for Japanese women exposed to low dose radiation from the atomic bombings. The risks should be reflected in protection standards.

Structure Property Studies for Additively Manufactured Parts

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

Milenski, Helen M; Schmalzer, Andrew Michael; Kelly, Daniel

2015-08-17

Since the invention of modern Additive Manufacturing (AM) processes engineers and designers have worked hard to capitalize on the unique building capabilities that AM allows. By being able to customize the interior fill of parts it is now possible to design components with a controlled density and customized internal structure. The creation of new polymers and polymer composites allow for even greater control over the mechanical properties of AM parts. One of the key reasons to explore AM, is to bring about a new paradigm in part design, where materials can be strategically optimized in a way that conventional subtractivemore » methods cannot achieve. The two processes investigated in my research were the Fused Deposition Modeling (FDM) process and the Direct Ink Write (DIW) process. The objectives of the research were to determine the impact of in-fill density and morphology on the mechanical properties of FDM parts, and to determine if DIW printed samples could be produced where the filament diameter was varied while the overall density remained constant.« less

Modeling the Effect of Geomorphic Change Triggered by Large Wood Addition on Salmon Habitat in a Forested Coastal Watershed

NASA Astrophysics Data System (ADS)

Bair, R.; Segura, C.; Lorion, C.

2015-12-01

Large wood (LW) additions are often part of fish habitat restorations in the PNW where historic forest clear-cutting limited natural wood recruitment. These efforts' relative successes are rarely reported in terms of ecological significance to different life stages of fish. Understanding the effectiveness of LW additions will contribute to successfully managing forest land. In this study we quantify the geomorphic change of a restoration project involving LW additions to three alluvial reaches in Mill Creek, OR. The reaches are 110-130m in plane-bed morphology and drain 2-16km2. We quantify the change in available habitat to different life stages of coho salmon in terms of velocity (v), shear stress (t), flow depth, and grain size distributions (GSD) considering existing thresholds in the literature for acceptable habitat. Flow conditions before and after LW additions are assessed using a 2D hydrodynamic model (FaSTMECH). Model inputs include detailed channel topography, discharge, and surface GSD. The spatial-temporal variability of sediment transport was also quantified based the modeled t distributions and the GSD to document changes in the overall geomorphic regime. Initial modeling results for pre wood conditions show mean t and v values ranging between 0 and 26N/m2 and between 0 and 2.4m/s, respectively for up to bankfull flow (Qbf). The distributions of both t and v become progressively wider and peak at higher values as flow increases with the notable exception at Qbf for which the area of low velocity increases noticeably. The spatial distributions of velocity results indicates that the extent of suitable habitat for adult coho decreased by 18% between flows 30 and 55% of BF. However the area of suitable habitat increased by 15% between 0.55Qbf and Qbf as the flow spreads from the channel into the floodplain. We expect the LW will enhance floodplain connectivity and thus available habitat by creating additional areas of low v during winter flows.

Structured functional additive regression in reproducing kernel Hilbert spaces

PubMed Central

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2013-01-01

Summary Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application. PMID:25013362

Intramolecular addition of cysteine thiyl radical to phenylalanine and tyrosine in model peptides, Phe (CysS•) and Tyr(CysS•): a computational study

PubMed Central

Naumov, Sergej; Schöneich, Christian

2009-01-01

Density Functional Theory (DFT) and ab initio calculations were carried out to evaluate the potential for intramolecular addition of cysteine (Cys) thiyl radicals (CysS•) to aromatic amino acids (Phe and Tyr) in water. These calculations yielded stable cyclic conformations, in which π-complexes were more stable than cyclohexadienyl radicals in water. In these π-complexes, the C2-S distances were significantly shorter compared to the C1-S and C3-S distances. Comparable results on the relative stabilities were obtained for model calculations for the addition of HS•/CH3S• to toluene and para-hydroxytoluene. The adduct of thiyl radicals with Phe was more stable than that with Tyr, and the stabilization energies depended on the C-terminal substituents. PMID:19309133

Study of mandible reconstruction using a fibula flap with application of additive manufacturing technology

PubMed Central

2014-01-01

Background This study aimed to establish surgical guiding techniques for completing mandible lesion resection and reconstruction of the mandible defect area with fibula sections in one surgery by applying additive manufacturing technology, which can reduce the surgical duration and enhance the surgical accuracy and success rate. Methods A computer assisted mandible reconstruction planning (CAMRP) program was used to calculate the optimal cutting length and number of fibula pieces and design the fixtures for mandible cutting, registration, and arrangement of the fibula segments. The mandible cutting and registering fixtures were then generated using an additive manufacturing system. The CAMRP calculated the optimal fibula cutting length and number of segments based on the location and length of the defective portion of the mandible. The mandible cutting jig was generated according to the boundary surface of the lesion resection on the mandible STL model. The fibular cutting fixture was based on the length of each segment, and the registered fixture was used to quickly arrange the fibula pieces into the shape of the defect area. In this study, the mandibular lesion was reconstructed using registered fibular sections in one step, and the method is very easy to perform. Results and conclusion The application of additive manufacturing technology provided customized models and the cutting fixtures and registered fixtures, which can improve the efficiency of clinical application. This study showed that the cutting fixture helped to rapidly complete lesion resection and fibula cutting, and the registered fixture enabled arrangement of the fibula pieces and allowed completion of the mandible reconstruction in a timely manner. Our method can overcome the disadvantages of traditional surgery, which requires a long and different course of treatment and is liable to cause error. With the help of optimal cutting planning by the CAMRP and the 3D printed mandible resection jig and

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate.

PubMed

Kamminga, Tjerko; Slagman, Simen-Jan; Bijlsma, Jetta J E; Martins Dos Santos, Vitor A P; Suarez-Diez, Maria; Schaap, Peter J

2017-10-01

Mycoplasma hyopneumoniae is cultured on large-scale to produce antigen for inactivated whole-cell vaccines against respiratory disease in pigs. However, the fastidious nutrient requirements of this minimal bacterium and the low growth rate make it challenging to reach sufficient biomass yield for antigen production. In this study, we sequenced the genome of M. hyopneumoniae strain 11 and constructed a high quality constraint-based genome-scale metabolic model of 284 chemical reactions and 298 metabolites. We validated the model with time-series data of duplicate fermentation cultures to aim for an integrated model describing the dynamic profiles measured in fermentations. The model predicted that 84% of cellular energy in a standard M. hyopneumoniae cultivation was used for non-growth associated maintenance and only 16% of cellular energy was used for growth and growth associated maintenance. Following a cycle of model-driven experimentation in dedicated fermentation experiments, we were able to increase the fraction of cellular energy used for growth through pyruvate addition to the medium. This increase in turn led to an increase in growth rate and a 2.3 times increase in the total biomass concentration reached after 3-4 days of fermentation, enhancing the productivity of the overall process. The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;114: 2339-2347. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Hierarchical additive modeling of nonlinear association with spatial correlations--an application to relate alcohol outlet density and neighborhood assault rates.

PubMed

Yu, Qingzhao; Li, Bin; Scribner, Richard Allen

2009-06-30

Previous studies have suggested a link between alcohol outlets and assaults. In this paper, we explore the effects of alcohol availability on assaults at the census tract level over time. In addition, we use a natural experiment to check whether a sudden loss of alcohol outlets is associated with deeper decreasing in assault violence. Several features of the data raise statistical challenges: (1) the association between covariates (for example, the alcohol outlet density of each census tract) and the assault rates may be complex and therefore cannot be described using a linear model without covariates transformation, (2) the covariates may be highly correlated with each other, (3) there are a number of observations that have missing inputs, and (4) there is spatial association in assault rates at the census tract level. We propose a hierarchical additive model, where the nonlinear correlations and the complex interaction effects are modeled using the multiple additive regression trees and the residual spatial association in the assault rates that cannot be explained in the model are smoothed using a conditional autoregressive (CAR) method. We develop a two-stage algorithm that connects the nonparametric trees with CAR to look for important covariates associated with the assault rates, while taking into account the spatial association of assault rates in adjacent census tracts. The proposed method is applied to the Los Angeles assault data (1990-1999). To assess the efficiency of the method, the results are compared with those obtained from a hierarchical linear model. Copyright (c) 2009 John Wiley & Sons, Ltd.

Additional follow-up telephone counselling and initial smoking relapse: a longitudinal, controlled study.

PubMed

Wu, Lei; He, Yao; Jiang, Bin; Zuo, Fang; Liu, Qinghui; Zhang, Li; Zhou, Changxi

2016-04-20

Smoking cessation services can help smokers to quit; however, many smoking relapse cases occur over time. Initial relapse prevention should play an important role in achieving the goal of long-term smoking cessation. Several studies have focused on the effect of extended telephone support in relapse prevention, but the conclusions remain conflicting. From October 2008 to August 2013, a longitudinal, controlled study was performed in a large general hospital of Beijing. The smokers who sought treatment at our smoking cessation clinic were non-randomised and divided into 2 groups: face-to-face individual counselling group (FC group), and face-to-face individual counselling plus telephone follow-up counselling group (FCF group). No pharmacotherapy was offered. The timing of initial smoking relapse was compared between FC and FCF groups. Predictors of initial relapse were investigated during the first 180 days, using the Cox proportional hazards model. Of 547 eligible male smokers who volunteered to participate, 457 participants (117 in FC group and 340 in FCF group) achieved at least 24 h abstinence. The majority of the lapse episodes occurred during the first 2 weeks after the quit date. Smokers who did not receive the follow-up telephone counselling (FC group) tended to relapse to smoking earlier than those smokers who received the additional follow-up telephone counselling (FCF group), and the log-rank test was statistically significant (p=0.003). A Cox regression model showed that, in the FCF group, being married, and having a lower Fagerström test score, normal body mass index and doctor-diagnosed tobacco-related chronic diseases, were significantly independent protective predictors of smoking relapse. Within the limitations of this study, it can be concluded that additional follow-up telephone counselling might be an effective strategy in preventing relapse. Further research is still needed to confirm our findings. Published by the BMJ Publishing Group

Radiation-induced hydroxyl addition to purine molecules: EPR and ENDOR study of hypoxanthine hydrochloride monohydrate single crystals.

PubMed

Tokdemir, Sibel; Nelson, William H

2005-06-01

Three radical species were detected in an EPR/ENDOR study of X-irradiated hypoxanthine.HCl.H2O single crystals at room temperature: RI was identified as the product of net H addition to C8, RII was identified as the product of net H addition to C2, and RIII was identified as the product of OH addition to C8. The observed set of radicals was the same for room-temperature irradiation as for irradiation at 10 K followed by warming the crystals to room temperature; however, the C2 H-addition and C8 OH-addition radicals were not detectable after storage of the crystals for about 2 months at room temperature. Use of selectively deuterated crystals permitted unique assignment of the observed hyperfine couplings, and results of density functional theory calculations on each of the radical structures were consistent with the experimental results. Comparison of these experimental results with others from previous crystal-based systems and model system computations provides insight into the mechanisms by which the biologically important purine C8 hydroxyl addition products are formed. The evidence from solid systems supports the mechanism of net water addition to one-electron oxidized purine bases and demonstrates the importance of a facial approach between the reactants.

Effects of some polymeric additives on the cocrystallization of caffeine

NASA Astrophysics Data System (ADS)

Chung, Jihae; Kim, Il Won

2011-11-01

Effects of polymeric additives on the model cocrystallization were examined. The model cocrystal was made from caffeine and oxalic acid, and poly(ethylene glycol) (PEG), poly( L-lactide) (PLLA), poly(ɛ-caprolactone) (PCL), and poly(acrylic acid) (PAA) were the additives. The cocrystals were formed as millimeter-sized crystals without additives, and they became microcrystals with PLLA and PCL, and nanocrystals with PAA. XRD and IR revealed that the cocrystal structure was unchanged despite the strong effects of the additives on the crystal morphology, although some decrease in crystallinity was observed with PAA as confirmed by DSC. The DSC study also showed that the cocrystal melted and recrystallized to form α-caffeine upon heating. The present study verified that the polymeric additives can be utilized to modulate the size and morphology of the cocrystals without interfering the intermolecular interactions essential to the integrity of the cocrystal structures.

The development, evaluation, and application of O3 flux and flux-response models for additional agricultural crops

Treesearch

L. D. Emberson; W. J. Massman; P. Buker; G. Soja; I. Van De Sand; G. Mills; C. Jacobs

2006-01-01

Currently, stomatal O3 flux and flux-response models only exist for wheat and potato (LRTAP Convention, 2004), as such there is a need to extend these models to include additional crop types. The possibility of establishing robust stomatal flux models for five agricultural crops (tomato, grapevine, sugar beet, maize and sunflower) was investigated. These crops were...

Additivity vs Synergism: Investigation of the Additive Interaction of Cinnamon Bark Oil and Meropenem in Combinatory Therapy.

PubMed

Yang, Shun-Kai; Yusoff, Khatijah; Mai, Chun-Wai; Lim, Wei-Meng; Yap, Wai-Sum; Lim, Swee-Hua Erin; Lai, Kok-Song

2017-11-04

Combinatory therapies have been commonly applied in the clinical setting to tackle multi-drug resistant bacterial infections and these have frequently proven to be effective. Specifically, combinatory therapies resulting in synergistic interactions between antibiotics and adjuvant have been the main focus due to their effectiveness, sidelining the effects of additivity, which also lowers the minimal effective dosage of either antimicrobial agent. Thus, this study was undertaken to look at the effects of additivity between essential oils and antibiotic, via the use of cinnamon bark essential oil (CBO) and meropenem as a model for additivity. Comparisons between synergistic and additive interaction of CBO were performed in terms of the ability of CBO to disrupt bacterial membrane, via zeta potential measurement, outer membrane permeability assay and scanning electron microscopy. It has been found that the additivity interaction between CBO and meropenem showed similar membrane disruption ability when compared to those synergistic combinations which was previously reported. Hence, results based on our studies strongly suggest that additive interaction acts on a par with synergistic interaction. Therefore, further investigation in additive interaction between antibiotics and adjuvant should be performed for a more in depth understanding of the mechanism and the impacts of such interaction.

Shape of the BMI-mortality association by cause of death, using generalized additive models: NHIS 1986-2006.

PubMed

Zajacova, Anna; Burgard, Sarah A

2012-03-01

Numerous studies have examined the association between body mass index (BMI) and mortality. The precise shape of their association, however, has not been established. We use nonparametric methods to determine the relationship between BMI and mortality. Data from the National Health Interview Survey-Linked Mortality Files 1986-2006 for adults aged 50 to 80 are analyzed using a Poisson approach to survival modeling within the generalized additive model (GAM) framework. The BMI-mortality association is more V shaped than U shaped, with the odds of dying rising steeply from the lowest risk point at BMIs of 23 to 26. The association varies considerably by time since interview and cause of death. For instance, the association has an inverted J shape for respiratory causes but is monotonically increasing for diabetes deaths. Our findings have implications for interpreting results from BMI-mortality studies and suggest caution in translating the findings into public health messages.

Additional Samples: Where They Should Be Located

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

Pilger, G. G., E-mail: jfelipe@ufrgs.br; Costa, J. F. C. L.; Koppe, J. C.

2001-09-15

Information for mine planning requires to be close spaced, if compared to the grid used for exploration and resource assessment. The additional samples collected during quasimining usually are located in the same pattern of the original diamond drillholes net but closer spaced. This procedure is not the best in mathematical sense for selecting a location. The impact of an additional information to reduce the uncertainty about the parameter been modeled is not the same everywhere within the deposit. Some locations are more sensitive in reducing the local and global uncertainty than others. This study introduces a methodology to select additionalmore » sample locations based on stochastic simulation. The procedure takes into account data variability and their spatial location. Multiple equally probable models representing a geological attribute are generated via geostatistical simulation. These models share basically the same histogram and the same variogram obtained from the original data set. At each block belonging to the model a value is obtained from the n simulations and their combination allows one to access local variability. Variability is measured using an uncertainty index proposed. This index was used to map zones of high variability. A value extracted from a given simulation is added to the original data set from a zone identified as erratic in the previous maps. The process of adding samples and simulation is repeated and the benefit of the additional sample is evaluated. The benefit in terms of uncertainty reduction is measure locally and globally. The procedure showed to be robust and theoretically sound, mapping zones where the additional information is most beneficial. A case study in a coal mine using coal seam thickness illustrates the method.« less

A study of the additional costs of dispensing workers' compensation prescriptions.

PubMed

Schafermeyer, Kenneth W

2007-03-01

Although there is a significant amount of additional work involved in dispensing workers' compensation prescriptions, these costs have not been quantified. A study of the additional costs to dispense a workers' compensation prescription is needed to measure actual costs and to help determine the reasonableness of reimbursement for prescriptions dispensed under workers' compensation programs. The purpose of this study was to determine the minimum additional time and costs required to dispense workers' compensation prescriptions in Texas. A convenience sample of 30 store-level pharmacy staff members involved in submitting and processing prescription claims for the Texas Mutual workers' compensation program were interviewed by telephone. Data collected to determine the additional costs of dispensing a workers' compensation prescription included (1) the amount of additional time and personnel costs required to dispense and process an average workers' compensation prescription claim, (2) the difference in time required for a new versus a refilled prescription, (3) overhead costs for processing workers' compensation prescription claims by experienced experts at a central processing facility, (4) carrying costs for workers' compensation accounts receivable, and (5) bad debts due to uncollectible workers' compensation claims. The median of the sample pharmacies' additional costs for dispensing a workers' compensation prescription was estimated to be at least $9.86 greater than for a cash prescription. This study shows that the estimated costs for workers' compensation prescriptions were significantly higher than for cash prescriptions. These costs are probably much more than most employers, workers' compensation payers, and pharmacy managers would expect. It is recommended that pharmacy managers should estimate their own costs and compare these costs to actual reimbursement when considering the reasonableness of workers' compensation prescriptions and whether to accept

Regional geoid computation by least squares modified Hotine's formula with additive corrections

NASA Astrophysics Data System (ADS)

Märdla, Silja; Ellmann, Artu; Ågren, Jonas; Sjöberg, Lars E.

2018-03-01

Geoid and quasigeoid modelling from gravity anomalies by the method of least squares modification of Stokes's formula with additive corrections is adapted for the usage with gravity disturbances and Hotine's formula. The biased, unbiased and optimum versions of least squares modification are considered. Equations are presented for the four additive corrections that account for the combined (direct plus indirect) effect of downward continuation (DWC), topographic, atmospheric and ellipsoidal corrections in geoid or quasigeoid modelling. The geoid or quasigeoid modelling scheme by the least squares modified Hotine formula is numerically verified, analysed and compared to the Stokes counterpart in a heterogeneous study area. The resulting geoid models and the additive corrections computed both for use with Stokes's or Hotine's formula differ most in high topography areas. Over the study area (reaching almost 2 km in altitude), the approximate geoid models (before the additive corrections) differ by 7 mm on average with a 3 mm standard deviation (SD) and a maximum of 1.3 cm. The additive corrections, out of which only the DWC correction has a numerically significant difference, improve the agreement between respective geoid or quasigeoid models to an average difference of 5 mm with a 1 mm SD and a maximum of 8 mm.

Serum Potassium and Glucose Regulation in the ADDITION-Leicester Screening Study

PubMed Central

Carter, Patrice; Bodicoat, Danielle H.; Quinn, Lauren M.; Zaccardi, Francesco; Webb, David R.; Khunti, Kamlesh; Davies, Melanie J.

2015-01-01

Introduction. Previous observational studies have shown conflicting results between plasma K+ concentrations and risk of type 2 diabetes. To help clarify the evidence we aimed to determine whether an association existed between serum K+ and glucose regulation within a UK multiethnic population. Methods. Participants were recruited as part of the ADDITION Leicester study, a population based screening study. Individuals from primary care between the age of 40 and 75 years if White European or 25 and 75 years if South Asian or Afro Caribbean were recruited. Tests for associations between baseline characteristics and K+ quartiles were conducted using linear regression models. Results. Data showed individuals in the lowest K+ quartile had significantly greater 2-hour glucose levels (0.53 mmol/L, 95% CI: 0.36 to 0.70, P ≤ 0.001) than those in the highest K+ quartile. This estimation did not change with adjustment for potential confounders. Conversely, participants in the lowest K+ quartile had a 0.14% lower HbA1c (95% CI −0.19 to −0.10: P ≤ 0.001) compared to those in the highest K+ quartile. Conclusion. This cross-sectional analysis demonstrated that lower K+ was associated with greater 2 hr glucose. The data supports the possibility that K+ may influence glucose regulation and further research is warranted. PMID:25883988

Evaluating cardiovascular mortality in type 2 diabetes patients: an analysis based on competing risks Markov chains and additive regression models.

PubMed

Rosato, Rosalba; Ciccone, G; Bo, S; Pagano, G F; Merletti, F; Gregori, D

2007-06-01

Type 2 diabetes represents a condition significantly associated with increased cardiovascular mortality. The aims of the study are: (i) to estimate the cumulative incidence function for cause-specific mortality using Cox and Aalen model; (ii) to describe how the prediction of cardiovascular or other causes mortality changes for patients with different pattern of covariates; (iii) to show if different statistical methods may give different results. Cox and Aalen additive regression model through the Markov chain approach, are used to estimate the cause-specific hazard for cardiovascular or other causes mortality in a cohort of 2865 type 2 diabetic patients without insulin treatment. The models are compared in the estimation of the risk of death for patients of different severity. For younger patients with a better covariates profile, the Cumulative Incidence Function estimated by Cox and Aalen model was almost the same; for patients with the worst covariates profile, models gave different results: at the end of follow-up cardiovascular mortality rate estimated by Cox and Aalen model was 0.26 [95% confidence interval (CI) = 0.21-0.31] and 0.14 (95% CI = 0.09-0.18). Standard Cox and Aalen model capture the risk process for patients equally well with average profiles of co-morbidities. The Aalen model, in addition, is shown to be better at identifying cause-specific risk of death for patients with more severe clinical profiles. This result is relevant in the development of analytic tools for research and resource management within diabetes care.

Accelerated cure of phenol-formaldehyde by the addition of cure accelerators : studies with model compounds

Treesearch

Linda F. Lorenz; Anthony C. Conner

2000-01-01

Fast curing phenol-formaldehyde (PF) resins could potentially allow wood to be bonded at higher moisture contents and at lower press temperatures than those currently used commercially. Recent reports in the literature have shown that the addition of esters, lactones, or organic carbonates increased the curing rate of PF resins. Several mechanisms have been proposed to...

Hydrogen atom addition to the surface of graphene nanoflakes: A density functional theory study

NASA Astrophysics Data System (ADS)

Tachikawa, Hiroto

2017-02-01

Polycyclic aromatic hydrocarbons (PAHs) provide a 2-dimensional (2D) reaction surface in 3-dimensional (3D) interstellar space and have been utilized as a model of graphene surfaces. In the present study, the reaction of PAHs with atomic hydrogen was investigated by means of density functional theory (DFT) to systematically elucidate the binding nature of atomic hydrogen to graphene nanoflakes. PAHs with n = 4-37 were chosen, where n indicates the number of benzene rings. Activation energies of hydrogen addition to the graphene surface were calculated to be 5.2-7.0 kcal/mol at the CAM-B3LYP/6-311G(d,p) level, which is almost constant for all PAHs. The binding energies of hydrogen atom were slightly dependent on the size (n): 14.8-28.5 kcal/mol. The absorption spectra showed that a long tail is generated at the low-energy region after hydrogen addition to the graphene surface. The electronic states of hydrogenated graphenes were discussed on the basis of theoretical results.

Making intelligent systems team players: Additional case studies

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.; Rhoads, Ron W.

1993-01-01

Observations from a case study of intelligent systems are reported as part of a multi-year interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. A series of studies were conducted to investigate issues in designing intelligent fault management systems in aerospace applications for effective human-computer interaction. The results of the initial study are documented in two NASA technical memoranda: TM 104738 Making Intelligent Systems Team Players: Case Studies and Design Issues, Volumes 1 and 2; and TM 104751, Making Intelligent Systems Team Players: Overview for Designers. The objective of this additional study was to broaden the investigation of human-computer interaction design issues beyond the focus on monitoring and fault detection in the initial study. The results of this second study are documented which is intended as a supplement to the original design guidance documents. These results should be of interest to designers of intelligent systems for use in real-time operations, and to researchers in the areas of human-computer interaction and artificial intelligence.

Air Pollution Exposure Modeling for Health Studies | Science ...

EPA Pesticide Factsheets

Dr. Michael Breen is leading the development of air pollution exposure models, integrated with novel personal sensor technologies, to improve exposure and risk assessments for individuals in health studies. He is co-investigator for multiple health studies assessing the exposure and effects of air pollutants. These health studies include participants with asthma, diabetes, and coronary artery disease living in various U.S. cities. He has developed, evaluated, and applied novel exposure modeling and time-activity tools, which includes the Exposure Model for Individuals (EMI), GPS-based Microenvironment Tracker (MicroTrac) and Exposure Tracker models. At this seminar, Dr. Breen will present the development and application of these models to predict individual-level personal exposures to particulate matter (PM) for two health studies in central North Carolina. These health studies examine the association between PM and adverse health outcomes for susceptible individuals. During Dr. Breen’s visit, he will also have the opportunity to establish additional collaborations with researchers at Harvard University that may benefit from the use of exposure models for cohort health studies. These research projects that link air pollution exposure with adverse health outcomes benefit EPA by developing model-predicted exposure-dose metrics for individuals in health studies to improve the understanding of exposure-response behavior of air pollutants, and to reduce participant

Study of the association of atmospheric temperature and relative humidity with bulk tank milk somatic cell count in dairy herds using Generalized additive mixed models.

PubMed

Testa, Francesco; Marano, Giuseppe; Ambrogi, Federico; Boracchi, Patrizia; Casula, Antonio; Biganzoli, Elia; Moroni, Paolo

2017-10-01

Elevated bulk tank milk somatic cell count (BMSCC) has a negative impact on milk production, milk quality, and animal health. Seasonal increases in herd level somatic cell count (SCC) are commonly associated with elevated environmental temperature and humidity. The Temperature Humidity Index (THI) has been developed to measure general environmental stress in dairy cattle; however, additional work is needed to determine a specific effect of the heat stress index on herd-level SCC. Generalized Additive Model methods were used for a flexible exploration of the relationships between daily temperature, relative humidity, and bulk milk somatic cell count. The data consist of BMSCC and meteorological recordings collected between March 2009 and October 2011 of 10 dairy farms. The results indicate that, an average increase of 0.16% of BMSCC is expected for an increase of 1°C degree of temperature. A complex relationship was found for relative humidity. For example, increase of 0.099%, 0.037% and 0.020% are expected in correspondence to an increase of relative humidity from 50% to 51%, 80% to 81%; and 90% to 91%, respectively. Using this model, it will be possible to provide evidence-based advice to dairy farmers for the use of THI control charts created on the basis of our statistical model. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Critical of the additive model of the randomized controlled trial].

PubMed

Boussageon, Rémy; Gueyffier, François; Bejan-Angoulvant, Theodora; Felden-Dominiak, Géraldine

2008-01-01

Randomized, double-blind, placebo-controlled clinical trials are currently the best way to demonstrate the clinical effectiveness of drugs. Its methodology relies on the method of difference (John Stuart Mill), through which the observed difference between two groups (drug vs placebo) can be attributed to the pharmacological effect of the drug being tested. However, this additive model can be questioned in the event of statistical interactions between the pharmacological and the placebo effects. Evidence in different domains has shown that the placebo effect can influence the effect of the active principle. This article evaluates the methodological, clinical and epistemological consequences of this phenomenon. Topics treated include extrapolating results, accounting for heterogeneous results, demonstrating the existence of several factors in the placebo effect, the necessity to take these factors into account for given symptoms or pathologies, as well as the problem of the "specific" effect.

Atmospheric numerical modeling resource enhancement and model convective parameterization/scale interaction studies

NASA Technical Reports Server (NTRS)

Cushman, Paula P.

1993-01-01

Research will be undertaken in this contract in the area of Modeling Resource and Facilities Enhancement to include computer, technical and educational support to NASA investigators to facilitate model implementation, execution and analysis of output; to provide facilities linking USRA and the NASA/EADS Computer System as well as resident work stations in ESAD; and to provide a centralized location for documentation, archival and dissemination of modeling information pertaining to NASA's program. Additional research will be undertaken in the area of Numerical Model Scale Interaction/Convective Parameterization Studies to include implementation of the comparison of cloud and rain systems and convective-scale processes between the model simulations and what was observed; and to incorporate the findings of these and related research findings in at least two refereed journal articles.

Skew-t partially linear mixed-effects models for AIDS clinical studies.

PubMed

Lu, Tao

2016-01-01

We propose partially linear mixed-effects models with asymmetry and missingness to investigate the relationship between two biomarkers in clinical studies. The proposed models take into account irregular time effects commonly observed in clinical studies under a semiparametric model framework. In addition, commonly assumed symmetric distributions for model errors are substituted by asymmetric distribution to account for skewness. Further, informative missing data mechanism is accounted for. A Bayesian approach is developed to perform parameter estimation simultaneously. The proposed model and method are applied to an AIDS dataset and comparisons with alternative models are performed.

Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Regression analysis of clustered failure time data with informative cluster size under the additive transformation models.

PubMed

Chen, Ling; Feng, Yanqin; Sun, Jianguo

2017-10-01

This paper discusses regression analysis of clustered failure time data, which occur when the failure times of interest are collected from clusters. In particular, we consider the situation where the correlated failure times of interest may be related to cluster sizes. For inference, we present two estimation procedures, the weighted estimating equation-based method and the within-cluster resampling-based method, when the correlated failure times of interest arise from a class of additive transformation models. The former makes use of the inverse of cluster sizes as weights in the estimating equations, while the latter can be easily implemented by using the existing software packages for right-censored failure time data. An extensive simulation study is conducted and indicates that the proposed approaches work well in both the situations with and without informative cluster size. They are applied to a dental study that motivated this study.

Using generalized additive modeling to empirically identify thresholds within the ITERS in relation to toddlers' cognitive development.

PubMed

Setodji, Claude Messan; Le, Vi-Nhuan; Schaack, Diana

2013-04-01

Research linking high-quality child care programs and children's cognitive development has contributed to the growing popularity of child care quality benchmarking efforts such as quality rating and improvement systems (QRIS). Consequently, there has been an increased interest in and a need for approaches to identifying thresholds, or cutpoints, in the child care quality measures used in these benchmarking efforts that differentiate between different levels of children's cognitive functioning. To date, research has provided little guidance to policymakers as to where these thresholds should be set. Using the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) data set, this study explores the use of generalized additive modeling (GAM) as a method of identifying thresholds on the Infant/Toddler Environment Rating Scale (ITERS) in relation to toddlers' performance on the Mental Development subscale of the Bayley Scales of Infant Development (the Bayley Mental Development Scale Short Form-Research Edition, or BMDSF-R). The present findings suggest that simple linear models do not always correctly depict the relationships between ITERS scores and BMDSF-R scores and that GAM-derived thresholds were more effective at differentiating among children's performance levels on the BMDSF-R. Additionally, the present findings suggest that there is a minimum threshold on the ITERS that must be exceeded before significant improvements in children's cognitive development can be expected. There may also be a ceiling threshold on the ITERS, such that beyond a certain level, only marginal increases in children's BMDSF-R scores are observed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Additive survival least square support vector machines: A simulation study and its application to cervical cancer prediction

NASA Astrophysics Data System (ADS)

Khotimah, Chusnul; Purnami, Santi Wulan; Prastyo, Dedy Dwi; Chosuvivatwong, Virasakdi; Sriplung, Hutcha

2017-11-01

Support Vector Machines (SVMs) has been widely applied for prediction in many fields. Recently, SVM is also developed for survival analysis. In this study, Additive Survival Least Square SVM (A-SURLSSVM) approach is used to analyze cervical cancer dataset and its performance is compared with the Cox model as a benchmark. The comparison is evaluated based on the prognostic index produced: concordance index (c-index), log rank, and hazard ratio. The higher prognostic index represents the better performance of the corresponding methods. This work also applied feature selection to choose important features using backward elimination technique based on the c-index criterion. The cervical cancer dataset consists of 172 patients. The empirical results show that nine out of the twelve features: age at marriage, age of first getting menstruation, age, parity, type of treatment, history of family planning, stadium, long-time of menstruation, and anemia status are selected as relevant features that affect the survival time of cervical cancer patients. In addition, the performance of the proposed method is evaluated through a simulation study with the different number of features and censoring percentages. Two out of three performance measures (c-index and hazard ratio) obtained from A-SURLSSVM consistently yield better results than the ones obtained from Cox model when it is applied on both simulated and cervical cancer data. Moreover, the simulation study showed that A-SURLSSVM performs better when the percentage of censoring data is small.

Toxicogenomics concepts and applications to study hepatic effects of food additives and chemicals

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

Stierum, Rob; Heijne, Wilbert; Kienhuis, Anne

2005-09-01

Transcriptomics, proteomics and metabolomics are genomics technologies with great potential in toxicological sciences. Toxicogenomics involves the integration of conventional toxicological examinations with gene, protein or metabolite expression profiles. An overview together with selected examples of the possibilities of genomics in toxicology is given. The expectations raised by toxicogenomics are earlier and more sensitive detection of toxicity. Furthermore, toxicogenomics will provide a better understanding of the mechanism of toxicity and may facilitate the prediction of toxicity of unknown compounds. Mechanism-based markers of toxicity can be discovered and improved interspecies and in vitro-in vivo extrapolations will drive model developments in toxicology. Toxicologicalmore » assessment of chemical mixtures will benefit from the new molecular biological tools. In our laboratory, toxicogenomics is predominantly applied for elucidation of mechanisms of action and discovery of novel pathway-supported mechanism-based markers of liver toxicity. In addition, we aim to integrate transcriptome, proteome and metabolome data, supported by bioinformatics to develop a systems biology approach for toxicology. Transcriptomics and proteomics studies on bromobenzene-mediated hepatotoxicity in the rat are discussed. Finally, an example is shown in which gene expression profiling together with conventional biochemistry led to the discovery of novel markers for the hepatic effects of the food additives butylated hydroxytoluene, curcumin, propyl gallate and thiabendazole.« less

Lumped mass model of a 1D metastructure for vibration suppression with no additional mass

NASA Astrophysics Data System (ADS)

Reichl, Katherine K.; Inman, Daniel J.

2017-09-01

The article examines the effectiveness of metastructures for vibration suppression from a weight standpoint. Metastructures, a metamaterial inspired concept, are structures with distributed vibration absorbers. In automotive and aerospace industries, it is critical to have low levels of vibrations while also using lightweight materials. Previous work has shown that metastructures are effective at mitigating vibrations, but do not consider the effects of mass. This work takes mass into consideration by comparing a structure with vibration absorbers to a structure of equal mass with no absorbers. These structures are modeled as one-dimensional lumped mass models, chosen for simplicity. Results compare both the steady-state and the transient responses. As a quantitative performance measure, the H2 norm, which is related to the area under the frequency response function, is calculated and compared for both the metastructure and the baseline structure. These results show that it is possible to obtain a favorable vibration response without adding additional mass to the structure. Additionally, the performance measure is utilized to optimize the geometry of the structure, determine the optimal ratio of mass in the absorber to mass of the host structure, and determine the frequencies of the absorbers. The dynamic response of this model is verified using a finite element analysis.

An introduction to modeling longitudinal data with generalized additive models: applications to single-case designs.

PubMed

Sullivan, Kristynn J; Shadish, William R; Steiner, Peter M

2015-03-01

Single-case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time in both the presence and absence of treatment. This article introduces a statistical technique for analyzing SCD data that has not been much used in psychological and educational research: generalized additive models (GAMs). In parametric regression, the researcher must choose a functional form to impose on the data, for example, that trend over time is linear. GAMs reverse this process by letting the data inform the choice of functional form. In this article we review the problem that trend poses in SCDs, discuss how current SCD analytic methods approach trend, describe GAMs as a possible solution, suggest a GAM model testing procedure for examining the presence of trend in SCDs, present a small simulation to show the statistical properties of GAMs, and illustrate the procedure on 3 examples of different lengths. Results suggest that GAMs may be very useful both as a form of sensitivity analysis for checking the plausibility of assumptions about trend and as a primary data analysis strategy for testing treatment effects. We conclude with a discussion of some problems with GAMs and some future directions for research on the application of GAMs to SCDs. (c) 2015 APA, all rights reserved).

Towards Additive Manufacture of Functional, Spline-Based Morphometric Models of Healthy and Diseased Coronary Arteries: In Vitro Proof-of-Concept Using a Porcine Template.

PubMed

Jewkes, Rachel; Burton, Hanna E; Espino, Daniel M

2018-02-02

The aim of this study is to assess the additive manufacture of morphometric models of healthy and diseased coronary arteries. Using a dissected porcine coronary artery, a model was developed with the use of computer aided engineering, with splines used to design arteries in health and disease. The model was altered to demonstrate four cases of stenosis displaying varying severity, based on published morphometric data available. Both an Objet Eden 250 printer and a Solidscape 3Z Pro printer were used in this analysis. A wax printed model was set into a flexible thermoplastic and was valuable for experimental testing with helical flow patterns observed in healthy models, dominating the distal LAD (left anterior descending) and left circumflex arteries. Recirculation zones were detected in all models, but were visibly larger in the stenosed cases. Resin models provide useful analytical tools for understanding the spatial relationships of blood vessels, and could be applied to preoperative planning techniques, but were not suitable for physical testing. In conclusion, it is feasible to develop blood vessel models enabling experimental work; further, through additive manufacture of bio-compatible materials, there is the possibility of manufacturing customized replacement arteries.

Towards Additive Manufacture of Functional, Spline-Based Morphometric Models of Healthy and Diseased Coronary Arteries: In Vitro Proof-of-Concept Using a Porcine Template

PubMed Central

Jewkes, Rachel; Burton, Hanna E.; Espino, Daniel M.

2018-01-01

The aim of this study is to assess the additive manufacture of morphometric models of healthy and diseased coronary arteries. Using a dissected porcine coronary artery, a model was developed with the use of computer aided engineering, with splines used to design arteries in health and disease. The model was altered to demonstrate four cases of stenosis displaying varying severity, based on published morphometric data available. Both an Objet Eden 250 printer and a Solidscape 3Z Pro printer were used in this analysis. A wax printed model was set into a flexible thermoplastic and was valuable for experimental testing with helical flow patterns observed in healthy models, dominating the distal LAD (left anterior descending) and left circumflex arteries. Recirculation zones were detected in all models, but were visibly larger in the stenosed cases. Resin models provide useful analytical tools for understanding the spatial relationships of blood vessels, and could be applied to preoperative planning techniques, but were not suitable for physical testing. In conclusion, it is feasible to develop blood vessel models enabling experimental work; further, through additive manufacture of bio-compatible materials, there is the possibility of manufacturing customized replacement arteries. PMID:29393899

Group additivity calculations of the thermodynamic properties of unfolded proteins in aqueous solution: a critical comparison of peptide-based and HKF models.

PubMed

Hakin, A W; Hedwig, G R

2001-02-15

A recent paper in this journal [Amend and Helgeson, Biophys. Chem. 84 (2000) 105] presented a new group additivity model to calculate various thermodynamic properties of unfolded proteins in aqueous solution. The parameters given for the revised Helgeson-Kirkham-Flowers (HKF) equations of state for all the constituent groups of unfolded proteins can be used, in principle, to calculate the partial molar heat capacity, C(o)p.2, and volume, V2(0), at infinite dilution of any polypeptide. Calculations of the values of C(o)p.2 and V2(0) for several polypeptides have been carried out to test the predictive utility of the HKF group additivity model. The results obtained are in very poor agreement with experimental data, and also with results calculated using a peptide-based group additivity model. A critical assessment of these two additivity models is presented.

RAMSEYS DRAFT WILDERNESS STUDY AREA AND ADDITION, VIRGINIA.

USGS Publications Warehouse

Lesure, Frank G.; Mory, Peter C.

1984-01-01

Mineral-resource surveys of the Ramseys Draft Wilderness Study Area and adjoining roadless area addition in George Washington National Forest in the western valley and ridge province, Augusta and Highland Counties, Virginia, were done. The surveys outlined three small areas containing anomalous amounts of copper, lead, and zinc related to stratabound red-bed copper mineralization, but these occurrences are not large and are not considered as having mineral-resource potential. The area contains abundant sandstone suitable for construction materials and shale suitable for making brick, tile, and other low-grade ceramic products, but these commodities occur in abundance outside the wilderness study area. Structural conditions are probably favorable for the accumulation of natural gas, but exploratory drilling has not been done sufficiently near the area to evaluate the gas potential.

A Bayesian additive model for understanding public transport usage in special events.

PubMed

Rodrigues, Filipe; Borysov, Stanislav; Ribeiro, Bernardete; Pereira, Francisco

2016-12-02

Public special events, like sports games, concerts and festivals are well known to create disruptions in transportation systems, often catching the operators by surprise. Although these are usually planned well in advance, their impact is difficult to predict, even when organisers and transportation operators coordinate. The problem highly increases when several events happen concurrently. To solve these problems, costly processes, heavily reliant on manual search and personal experience, are usual practice in large cities like Singapore, London or Tokyo. This paper presents a Bayesian additive model with Gaussian process components that combines smart card records from public transport with context information about events that is continuously mined from the Web. We develop an efficient approximate inference algorithm using expectation propagation, which allows us to predict the total number of public transportation trips to the special event areas, thereby contributing to a more adaptive transportation system. Furthermore, for multiple concurrent event scenarios, the proposed algorithm is able to disaggregate gross trip counts into their most likely components related to specific events and routine behavior. Using real data from Singapore, we show that the presented model outperforms the best baseline model by up to 26% in R2 and also has explanatory power for its individual components.

Regression Analysis of Mixed Recurrent-Event and Panel-Count Data with Additive Rate Models

PubMed Central

Zhu, Liang; Zhao, Hui; Sun, Jianguo; Leisenring, Wendy; Robison, Leslie L.

2015-01-01

Summary Event-history studies of recurrent events are often conducted in fields such as demography, epidemiology, medicine, and social sciences (Cook and Lawless, 2007; Zhao et al., 2011). For such analysis, two types of data have been extensively investigated: recurrent-event data and panel-count data. However, in practice, one may face a third type of data, mixed recurrent-event and panel-count data or mixed event-history data. Such data occur if some study subjects are monitored or observed continuously and thus provide recurrent-event data, while the others are observed only at discrete times and hence give only panel-count data. A more general situation is that each subject is observed continuously over certain time periods but only at discrete times over other time periods. There exists little literature on the analysis of such mixed data except that published by Zhu et al. (2013). In this paper, we consider the regression analysis of mixed data using the additive rate model and develop some estimating equation-based approaches to estimate the regression parameters of interest. Both finite sample and asymptotic properties of the resulting estimators are established, and the numerical studies suggest that the proposed methodology works well for practical situations. The approach is applied to a Childhood Cancer Survivor Study that motivated this study. PMID:25345405

The effect of different levels of sunflower head pith addition on the properties of model system emulsions prepared from fresh and frozen beef.

PubMed

Sariçoban, Cemalettin; Yilmaz, Mustafa Tahsin; Karakaya, Mustafa; Tiske, Sümeyra Sultan

2010-01-01

The effect of sunflower head pith on the functional properties of emulsions was studied by using a model system. Oil/water (O/W) model emulsion systems were prepared from fresh and frozen beef by the addition of the pith at five concentrations. Emulsion capacity (EC), stability (ES), viscosity (EV), colour and flow properties of the prepared model system emulsions were analyzed. The pith addition increased the EC and ES and the highest EC and ES values were reached when 5% of pith added; however, further increase in the pith concentration caused an inverse trend in these values. Fresh beef emulsions had higher EC and ES values than did frozen beef emulsions. One percent pith concentration was the critic level for the EV values of fresh beef emulsions. EV values of the emulsions reached a maximum level at 5% pith level, followed by a decrease at 7% pit level.

Modeling a Change in Flowrate through Detention or Additional Pavement on the Receiving Stream : Final Report

DOT National Transportation Integrated Search

2017-11-01

The addition or removal of flow from a stream affects the water surface downstream and possibly upstream. The extent of such effects is generally determined by modeling the receiving stream. Guidance that concisely describes how far up/downstream a h...

78 FR 32224 - Availability of Version 3.1.2 of the Connect America Fund Phase II Cost Model; Additional...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-29

... Version 3.1.2 of the Connect America Fund Phase II Cost Model; Additional Discussion Topics in Connect America Cost Model Virtual Workshop AGENCY: Federal Communications Commission. ACTION: Proposed rule... America Cost Model (CAM v3.1.2), which allows Commission staff and interested parties to calculate costs...

The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing

PubMed Central

Rijkhorst, Erik-Jan; Hofman, Mark; Forouzanfar, Tymour; Wolff, Jan

2016-01-01

Objectives: Additively manufactured bone models, implants and drill guides are becoming increasingly popular amongst maxillofacial surgeons and dentists. To date, such constructs are commonly manufactured using CT technology that induces ionizing radiation. Recently, ultrashort echo time (UTE) MRI sequences have been developed that allow radiation-free imaging of facial bones. The aim of the present study was to assess the feasibility of UTE MRI sequences for medical additive manufacturing (AM). Methods: Three morphologically different dry human mandibles were scanned using a CT and MRI scanner. Additionally, optical scans of all three mandibles were made to acquire a “gold standard”. All CT and MRI scans were converted into Standard Tessellation Language (STL) models and geometrically compared with the gold standard. To quantify the accuracy of the AM process, the CT, MRI and gold-standard STL models of one of the mandibles were additively manufactured, optically scanned and compared with the original gold-standard STL model. Results: Geometric differences between all three CT-derived STL models and the gold standard were <1.0 mm. All three MRI-derived STL models generally presented deviations <1.5 mm in the symphyseal and mandibular area. The AM process introduced minor deviations of <0.5 mm. Conclusions: This study demonstrates that MRI using UTE sequences is a feasible alternative to CT in generating STL models of the mandible and would therefore be suitable for surgical planning and AM. Further in vivo studies are necessary to assess the usability of UTE MRI sequences in clinical settings. PMID:26943179

The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing.

PubMed

van Eijnatten, Maureen; Rijkhorst, Erik-Jan; Hofman, Mark; Forouzanfar, Tymour; Wolff, Jan

2016-01-01

Additively manufactured bone models, implants and drill guides are becoming increasingly popular amongst maxillofacial surgeons and dentists. To date, such constructs are commonly manufactured using CT technology that induces ionizing radiation. Recently, ultrashort echo time (UTE) MRI sequences have been developed that allow radiation-free imaging of facial bones. The aim of the present study was to assess the feasibility of UTE MRI sequences for medical additive manufacturing (AM). Three morphologically different dry human mandibles were scanned using a CT and MRI scanner. Additionally, optical scans of all three mandibles were made to acquire a "gold standard". All CT and MRI scans were converted into Standard Tessellation Language (STL) models and geometrically compared with the gold standard. To quantify the accuracy of the AM process, the CT, MRI and gold-standard STL models of one of the mandibles were additively manufactured, optically scanned and compared with the original gold-standard STL model. Geometric differences between all three CT-derived STL models and the gold standard were <1.0 mm. All three MRI-derived STL models generally presented deviations <1.5 mm in the symphyseal and mandibular area. The AM process introduced minor deviations of <0.5 mm. This study demonstrates that MRI using UTE sequences is a feasible alternative to CT in generating STL models of the mandible and would therefore be suitable for surgical planning and AM. Further in vivo studies are necessary to assess the usability of UTE MRI sequences in clinical settings.

A Mathematical Study on “Additive Technique” Versus “Branch and Bound Technique” for Solving Binary Programming Problem

NASA Astrophysics Data System (ADS)

Sufahani, Suliadi; Ghazali Kamardan, M.; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Khalid, Kamil; Ali, Maselan; Khalid, Kamal; Nawawi, MKM; Ahmad, Asmala

2018-04-01

A solid body needs adequate supplements from nourishment that we eat each day. Eating pretty much than what our body needs will prompt lack of healthy sustenance (under-nourishment and over-nourishment). In Malaysia, a few reviews have been directed to examine the wholesome status of Malaysians, particularly among youngsters and youths. However there are different methods for taking care of the menu arranging issue and in this paper Binary Programming (BP) is executed. Separately, “Additive Technique (AT)” and “Branch and Bound Technique (BBT)” are utilized as a part of BP. Both methodologies utilize diverse systems and might yield distinctive ideal arrangements. Along these lines, this study expects to build up a scientific model for eating regimen arranging that meets the essential supplement admission and look at the outcomes yield through additive substance and branch and bound methodologies. The information was gathered from different all inclusive schools and furthermore from the Ministry of Education. The model was illuminated by utilizing the Balas Algorithm through AT and Binary Programming through BBT.

A comparative study of additive and subtractive manufacturing for dental restorations.

PubMed

Bae, Eun-Jeong; Jeong, Il-Do; Kim, Woong-Chul; Kim, Ji-Hwan

2017-08-01

Digital systems have recently found widespread application in the fabrication of dental restorations. For the clinical assessment of dental restorations fabricated digitally, it is necessary to evaluate their accuracy. However, studies of the accuracy of inlay restorations fabricated with additive manufacturing are lacking. The purpose of this in vitro study was to evaluate and compare the accuracy of inlay restorations fabricated by using recently introduced additive manufacturing with the accuracy of subtractive methods. The inlay (distal occlusal cavity) shape was fabricated using 3-dimensional image (reference data) software. Specimens were fabricated using 4 different methods (each n=10, total N=40), including 2 additive manufacturing methods, stereolithography apparatus and selective laser sintering; and 2 subtractive methods, wax and zirconia milling. Fabricated specimens were scanned using a dental scanner and then compared by overlapping reference data. The results were statistically analyzed using a 1-way analysis of variance (α=.05). Additionally, the surface morphology of 1 randomly (the first of each specimen) selected specimen from each group was evaluated using a digital microscope. The results of the overlap analysis of the dental restorations indicated that the root mean square (RMS) deviation observed in the restorations fabricated using the additive manufacturing methods were significantly different from those fabricated using the subtractive methods (P<.05). However, no significant differences were found between restorations fabricated using stereolithography apparatus and selective laser sintering, the additive manufacturing methods (P=.466). Similarly, no significant differences were found between wax and zirconia, the subtractive methods (P=.986). The observed RMS values were 106 μm for stereolithography apparatus, 113 μm for selective laser sintering, 116 μm for wax, and 119 μm for zirconia. Microscopic evaluation of the surface

Worst case prediction of additives migration from polystyrene for food safety purposes: a model update.

PubMed

Martínez-López, Brais; Gontard, Nathalie; Peyron, Stéphane

2018-03-01

A reliable prediction of migration levels of plastic additives into food requires a robust estimation of diffusivity. Predictive modelling of diffusivity as recommended by the EU commission is carried out using a semi-empirical equation that relies on two polymer-dependent parameters. These parameters were determined for the polymers most used by packaging industry (LLDPE, HDPE, PP, PET, PS, HIPS) from the diffusivity data available at that time. In the specific case of general purpose polystyrene, the diffusivity data published since then shows that the use of the equation with the original parameters results in systematic underestimation of diffusivity. The goal of this study was therefore, to propose an update of the aforementioned parameters for PS on the basis of up to date diffusivity data, so the equation can be used for a reasoned overestimation of diffusivity.

Applying additive modeling and gradient boosting to assess the effects of watershed and reach characteristics on riverine assemblages

USGS Publications Warehouse

Maloney, Kelly O.; Schmid, Matthias; Weller, Donald E.

2012-01-01

Issues with ecological data (e.g. non-normality of errors, nonlinear relationships and autocorrelation of variables) and modelling (e.g. overfitting, variable selection and prediction) complicate regression analyses in ecology. Flexible models, such as generalized additive models (GAMs), can address data issues, and machine learning techniques (e.g. gradient boosting) can help resolve modelling issues. Gradient boosted GAMs do both. Here, we illustrate the advantages of this technique using data on benthic macroinvertebrates and fish from 1573 small streams in Maryland, USA.

Ultimate strength performance of tankers associated with industry corrosion addition practices

NASA Astrophysics Data System (ADS)

Kim, Do Kyun; Kim, Han Byul; Zhang, Xiaoming; Li, Chen Guang; Paik, Jeom Kee

2014-09-01

In the ship and offshore structure design, age-related problems such as corrosion damage, local denting, and fatigue damage are important factors to be considered in building a reliable structure as they have a significant influence on the residual structural capacity. In shipping, corrosion addition methods are widely adopted in structural design to prevent structural capacity degradation. The present study focuses on the historical trend of corrosion addition rules for ship structural design and investigates their effects on the ultimate strength performance such as hull girder and stiffened panel of double hull oil tankers. Three types of rules based on corrosion addition models, namely historic corrosion rules (pre-CSR), Common Structural Rules (CSR), and harmonised Common Structural Rules (CSRH) are considered and compared with two other corrosion models namely UGS model, suggested by the Union of Greek Shipowners (UGS), and Time-Dependent Corrosion Wastage Model (TDCWM). To identify the general trend in the effects of corrosion damage on the ultimate longitudinal strength performance, the corrosion addition rules are applied to four representative sizes of double hull oil tankers namely Panamax, Aframax, Suezmax, and VLCC. The results are helpful in understanding the trend of corrosion additions for tanker structures

Topsoil organic carbon content of Europe, a new map based on a generalised additive model

NASA Astrophysics Data System (ADS)

de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

2014-05-01

There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average

Recommended Protocol for Round Robin Studies in Additive Manufacturing

PubMed Central

Moylan, Shawn; Brown, Christopher U.; Slotwinski, John

2016-01-01

One way to improve confidence and encourage proliferation of additive manufacturing (AM) technologies and parts is by generating more high quality data describing the performance of AM processes and parts. Many in the AM community see round robin studies as a way to generate large data sets while distributing the cost among the participants, thereby reducing the cost to individual users. The National Institute of Standards and Technology (NIST) has conducted and participated in several of these AM round robin studies. While the results of these studies are interesting and informative, many of the lessons learned in conducting these studies concern the logistics and methods of the study and unique issues presented by AM. Existing standards for conducting interlaboratory studies of measurement methods, along with NIST’s experience, form the basis for recommended protocols for conducting AM round robin studies. The role of round robin studies in AM qualification, some of the limitations of round robin studies, and the potential benefit of less formal collaborative experiments where multiple factors, AM machine being only one, are varied simultaneously are also discussed. PMID:27274602

Recommended Protocol for Round Robin Studies in Additive Manufacturing.

PubMed

Moylan, Shawn; Brown, Christopher U; Slotwinski, John

2016-03-01

One way to improve confidence and encourage proliferation of additive manufacturing (AM) technologies and parts is by generating more high quality data describing the performance of AM processes and parts. Many in the AM community see round robin studies as a way to generate large data sets while distributing the cost among the participants, thereby reducing the cost to individual users. The National Institute of Standards and Technology (NIST) has conducted and participated in several of these AM round robin studies. While the results of these studies are interesting and informative, many of the lessons learned in conducting these studies concern the logistics and methods of the study and unique issues presented by AM. Existing standards for conducting interlaboratory studies of measurement methods, along with NIST's experience, form the basis for recommended protocols for conducting AM round robin studies. The role of round robin studies in AM qualification, some of the limitations of round robin studies, and the potential benefit of less formal collaborative experiments where multiple factors, AM machine being only one, are varied simultaneously are also discussed.

Modeling the Impact of School-based Universal Depression Screening on Additional Service Capacity Needs: A System Dynamics Approach

PubMed Central

Lyon, Aaron R.; Maras, Melissa A.; Pate, Christina M.; Igusa, Takeru; Stoep, Ann Vander

2016-01-01

Although it is widely known that the occurrence of depression increases over the course of adolescence, symptoms of mood disorders frequently go undetected. While schools are viable settings for conducting universal screening to systematically identify students in need of services for common health conditions, particularly those that adversely affect school performance, few school districts routinely screen their students for depression. Among the most commonly referenced barriers are concerns that the number of students identified may exceed schools’ service delivery capacities, but few studies have evaluated this concern systematically. System dynamics (SD) modeling may prove a useful approach for answering questions of this sort. The goal of the current paper is therefore to demonstrate how SD modeling can be applied to inform implementation decisions in communities. In our demonstration, we used SD modeling to estimate the additional service demand generated by universal depression screening in a typical high school. We then simulated the effects of implementing “compensatory approaches” designed to address anticipated increases in service need through (1) the allocation of additional staff time and (2) improvements in the effectiveness of mental health interventions. Results support the ability of screening to facilitate more rapid entry into services and suggest that improving the effectiveness of mental health services for students with depression via the implementation of an evidence-based treatment protocol may have a limited impact on overall recovery rates and service availability. In our example, the SD approach proved useful in informing systems’ decision-making about the adoption of a new school mental health service. PMID:25601192

A study of vibrating nanotubes with additional adsorbed masses

NASA Astrophysics Data System (ADS)

Adler, Joan; Adler, Omri

2017-11-01

We describe calculations of the electronic density surrounding strained nanotubes. These are then used to estimate the nanotube wall width. This width is an essential parameter for the analysis of the nanotube vibrations. By studying the effect of additional adsorbed molecules on the nanotubes’ vibrations and their frequency changes we can deduce the molecules’ mass. Our calculations show that the strain does not greatly affect the nanotube width, but the vibrations change sufficiently for the mass to be detected.

Modeling of Processing-Induced Pore Morphology in an Additively-Manufactured Ti-6Al-4V Alloy

PubMed Central

Kabir, Mohammad Rizviul; Richter, Henning

2017-01-01

A selective laser melting (SLM)-based, additively-manufactured Ti-6Al-4V alloy is prone to the accumulation of undesirable defects during layer-by-layer material build-up. Defects in the form of complex-shaped pores are one of the critical issues that need to be considered during the processing of this alloy. Depending on the process parameters, pores with concave or convex boundaries may occur. To exploit the full potential of additively-manufactured Ti-6Al-4V, the interdependency between the process parameters, pore morphology, and resultant mechanical properties, needs to be understood. By incorporating morphological details into numerical models for micromechanical analyses, an in-depth understanding of how these pores interact with the Ti-6Al-4V microstructure can be gained. However, available models for pore analysis lack a realistic description of both the Ti-6Al-4V grain microstructure, and the pore geometry. To overcome this, we propose a comprehensive approach for modeling and discretizing pores with complex geometry, situated in a polycrystalline microstructure. In this approach, the polycrystalline microstructure is modeled by means of Voronoi tessellations, and the complex pore geometry is approximated by strategically combining overlapping spheres of varied sizes. The proposed approach provides an elegant way to model the microstructure of SLM-processed Ti-6Al-4V containing pores or crack-like voids, and makes it possible to investigate the relationship between process parameters, pore morphology, and resultant mechanical properties in a finite-element-based simulation framework. PMID:28772504

Modeling of Processing-Induced Pore Morphology in an Additively-Manufactured Ti-6Al-4V Alloy.

PubMed

Kabir, Mohammad Rizviul; Richter, Henning

2017-02-08

A selective laser melting (SLM)-based, additively-manufactured Ti-6Al-4V alloy is prone to the accumulation of undesirable defects during layer-by-layer material build-up. Defects in the form of complex-shaped pores are one of the critical issues that need to be considered during the processing of this alloy. Depending on the process parameters, pores with concave or convex boundaries may occur. To exploit the full potential of additively-manufactured Ti-6Al-4V, the interdependency between the process parameters, pore morphology, and resultant mechanical properties, needs to be understood. By incorporating morphological details into numerical models for micromechanical analyses, an in-depth understanding of how these pores interact with the Ti-6Al-4V microstructure can be gained. However, available models for pore analysis lack a realistic description of both the Ti-6Al-4V grain microstructure, and the pore geometry. To overcome this, we propose a comprehensive approach for modeling and discretizing pores with complex geometry, situated in a polycrystalline microstructure. In this approach, the polycrystalline microstructure is modeled by means of Voronoi tessellations, and the complex pore geometry is approximated by strategically combining overlapping spheres of varied sizes. The proposed approach provides an elegant way to model the microstructure of SLM-processed Ti-6Al-4V containing pores or crack-like voids, and makes it possible to investigate the relationship between process parameters, pore morphology, and resultant mechanical properties in a finite-element-based simulation framework.

Use of generalised additive models to categorise continuous variables in clinical prediction

PubMed Central

2013-01-01

Background In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. Methods We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high- and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. Results The three-category proposal for the respiratory rate was ≤ 20;(20,24];> 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically

Stability improvement of natural food colors: Impact of amino acid and peptide addition on anthocyanin stability in model beverages.

PubMed

Chung, Cheryl; Rojanasasithara, Thananunt; Mutilangi, William; McClements, David Julian

2017-03-01

Anthocyanins are prone to chemical degradation and color fading in the presence of vitamin C. The potential of three amino acids (l-phenylalanine, l-tyrosine, l-tryptophan) and a polypeptide (ε-poly-l-lysine) in prolonging the color stability of purple carrot anthocyanins (0.025%) in model beverages (0.05% l-ascorbic acid, citric acid, pH 3.0) stored at elevated temperature (40°C/7 days) was examined. In the absence of amino acids or peptides, anthocyanin degraded at first-order reaction rate. Addition of amino acids or peptide (0.1%) increased the color stability of anthocyanins, with the most significant improvement observed for l-tryptophan. The average half-life of anthocyanin color increased from 2 days to 6 days with l-tryptophan addition. Fluorescence quenching measurements revealed that the l-tryptophan interacted with anthocyanins mainly through hydrogen bonding, although some hydrophobic interaction may also have been involved. Overall, this study suggests that amino acid or peptide addition may prolong the color stability of anthocyanin in beverage products. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic modeling for rigid rotor bearing systems with a localized defect considering additional deformations at the sharp edges

NASA Astrophysics Data System (ADS)

Liu, Jing; Shao, Yimin

2017-06-01

Rotor bearing systems (RBSs) play a very valuable role for wind turbine gearboxes, aero-engines, high speed spindles, and other rotational machinery. An in-depth understanding of vibrations of the RBSs is very useful for condition monitoring and diagnosis applications of these machines. A new twelve-degree-of-freedom dynamic model for rigid RBSs with a localized defect (LOD) is proposed. This model can formulate the housing support stiffness, interfacial frictional moments including load dependent and load independent components, time-varying displacement excitation caused by a LOD, additional deformations at the sharp edges of the LOD, and lubricating oil film. The time-varying displacement model is determined by a half-sine function. A new method for calculating the additional deformations at the sharp edges of the LOD is analytical derived based on an elastic quarter-space method presented in the literature. The proposed dynamic model is utilized to analyze the influences of the housing support stiffness and LOD sizes on the vibration characteristics of the rigid RBS, which cannot be predicted by the previous dynamic models in the literature. The results show that the presented method can give a new dynamic modeling method for vibration formulation for a rigid RBS with and without the LOD on the races.

Regression analysis of mixed recurrent-event and panel-count data with additive rate models.

PubMed

Zhu, Liang; Zhao, Hui; Sun, Jianguo; Leisenring, Wendy; Robison, Leslie L

2015-03-01

Event-history studies of recurrent events are often conducted in fields such as demography, epidemiology, medicine, and social sciences (Cook and Lawless, 2007, The Statistical Analysis of Recurrent Events. New York: Springer-Verlag; Zhao et al., 2011, Test 20, 1-42). For such analysis, two types of data have been extensively investigated: recurrent-event data and panel-count data. However, in practice, one may face a third type of data, mixed recurrent-event and panel-count data or mixed event-history data. Such data occur if some study subjects are monitored or observed continuously and thus provide recurrent-event data, while the others are observed only at discrete times and hence give only panel-count data. A more general situation is that each subject is observed continuously over certain time periods but only at discrete times over other time periods. There exists little literature on the analysis of such mixed data except that published by Zhu et al. (2013, Statistics in Medicine 32, 1954-1963). In this article, we consider the regression analysis of mixed data using the additive rate model and develop some estimating equation-based approaches to estimate the regression parameters of interest. Both finite sample and asymptotic properties of the resulting estimators are established, and the numerical studies suggest that the proposed methodology works well for practical situations. The approach is applied to a Childhood Cancer Survivor Study that motivated this study. © 2014, The International Biometric Society.

Tackling Missing Data in Community Health Studies Using Additive LS-SVM Classifier.

PubMed

Wang, Guanjin; Deng, Zhaohong; Choi, Kup-Sze

2018-03-01

Missing data is a common issue in community health and epidemiological studies. Direct removal of samples with missing data can lead to reduced sample size and information bias, which deteriorates the significance of the results. While data imputation methods are available to deal with missing data, they are limited in performance and could introduce noises into the dataset. Instead of data imputation, a novel method based on additive least square support vector machine (LS-SVM) is proposed in this paper for predictive modeling when the input features of the model contain missing data. The method also determines simultaneously the influence of the features with missing values on the classification accuracy using the fast leave-one-out cross-validation strategy. The performance of the method is evaluated by applying it to predict the quality of life (QOL) of elderly people using health data collected in the community. The dataset involves demographics, socioeconomic status, health history, and the outcomes of health assessments of 444 community-dwelling elderly people, with 5% to 60% of data missing in some of the input features. The QOL is measured using a standard questionnaire of the World Health Organization. Results show that the proposed method outperforms four conventional methods for handling missing data-case deletion, feature deletion, mean imputation, and K-nearest neighbor imputation, with the average QOL prediction accuracy reaching 0.7418. It is potentially a promising technique for tackling missing data in community health research and other applications.

7 CFR 1710.253 - Engineering and cost studies-addition of generation capacity.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Engineering and cost studies-addition of generation... TO ELECTRIC LOANS AND GUARANTEES Construction Work Plans and Related Studies § 1710.253 Engineering... engineering and cost studies as specified by RUS. The studies shall cover a period from the beginning of the...

7 CFR 1710.253 - Engineering and cost studies-addition of generation capacity.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Engineering and cost studies-addition of generation... TO ELECTRIC LOANS AND GUARANTEES Construction Work Plans and Related Studies § 1710.253 Engineering... engineering and cost studies as specified by RUS. The studies shall cover a period from the beginning of the...

7 CFR 1710.253 - Engineering and cost studies-addition of generation capacity.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Engineering and cost studies-addition of generation... TO ELECTRIC LOANS AND GUARANTEES Construction Work Plans and Related Studies § 1710.253 Engineering... engineering and cost studies as specified by RUS. The studies shall cover a period from the beginning of the...

7 CFR 1710.253 - Engineering and cost studies-addition of generation capacity.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Engineering and cost studies-addition of generation... TO ELECTRIC LOANS AND GUARANTEES Construction Work Plans and Related Studies § 1710.253 Engineering... engineering and cost studies as specified by RUS. The studies shall cover a period from the beginning of the...

7 CFR 1710.253 - Engineering and cost studies-addition of generation capacity.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Engineering and cost studies-addition of generation... TO ELECTRIC LOANS AND GUARANTEES Construction Work Plans and Related Studies § 1710.253 Engineering... engineering and cost studies as specified by RUS. The studies shall cover a period from the beginning of the...

Addition of a Hydrological Cycle to the EPIC Jupiter Model

NASA Astrophysics Data System (ADS)

Dowling, T. E.; Palotai, C. J.

2002-09-01

We present a progress report on the development of the EPIC atmospheric model to include clouds, moist convection, and precipitation. Two major goals are: i) to study the influence that convective water clouds have on Jupiter's jets and vortices, such as those to the northwest of the Great Red Spot, and ii) to predict ammonia-cloud evolution for direct comparison to visual images (instead of relying on surrogates for clouds like potential vorticity). Data structures in the model are now set up to handle the vapor, liquid, and solid phases of the most common chemical species in planetary atmospheres. We have adapted the Prather conservation of second-order moments advection scheme to the model, which yields high accuracy for dealing with cloud edges. In collaboration with computer scientists H. Dietz and T. Mattox at the U. Kentucky, we have built a dedicated 40-node parallel computer that achieves 34 Gflops (double precision) at 74 cents per Mflop, and have updated the EPIC-model code to use cache-aware memory layouts and other modern optimizations. The latest test-case results of cloud evolution in the model will be presented. This research is funded by NASA's Planetary Atmospheres and EPSCoR programs.

Sequential neural processes in abacus mental addition: an EEG and FMRI case study.

PubMed

Ku, Yixuan; Hong, Bo; Zhou, Wenjing; Bodner, Mark; Zhou, Yong-Di

2012-01-01

Abacus experts are able to mentally calculate multi-digit numbers rapidly. Some behavioral and neuroimaging studies have suggested a visuospatial and visuomotor strategy during abacus mental calculation. However, no study up to now has attempted to dissociate temporally the visuospatial neural process from the visuomotor neural process during abacus mental calculation. In the present study, an abacus expert performed the mental addition tasks (8-digit and 4-digit addends presented in visual or auditory modes) swiftly and accurately. The 100% correct rates in this expert's task performance were significantly higher than those of ordinary subjects performing 1-digit and 2-digit addition tasks. ERPs, EEG source localizations, and fMRI results taken together suggested visuospatial and visuomotor processes were sequentially arranged during the abacus mental addition with visual addends and could be dissociated from each other temporally. The visuospatial transformation of the numbers, in which the superior parietal lobule was most likely involved, might occur first (around 380 ms) after the onset of the stimuli. The visuomotor processing, in which the superior/middle frontal gyri were most likely involved, might occur later (around 440 ms). Meanwhile, fMRI results suggested that neural networks involved in the abacus mental addition with auditory stimuli were similar to those in the visual abacus mental addition. The most prominently activated brain areas in both conditions included the bilateral superior parietal lobules (BA 7) and bilateral middle frontal gyri (BA 6). These results suggest a supra-modal brain network in abacus mental addition, which may develop from normal mental calculation networks.

The impact of tobacco additives on cigarette smoke toxicity: a critical appraisal of tobacco industry studies.

PubMed

Paumgartten, Francisco José Roma; Gomes-Carneiro, Maria Regina; Oliveira, Ana Cecilia Amado Xavier de

2017-09-21

Cigarette production involves a number of substances and materials other than just tobacco, paper and a filter. Tobacco additives include flavorings, enhancers, humectants, sugars, and ammonium compounds. Although companies maintain that tobacco additives do not enhance smoke toxicity and do not make cigarettes more attractive or addictive, these claims are questioned by independent researchers. This study reviewed the studies on the effects of tobacco additives on smoke chemistry and toxicity. Tobacco additives lead to higher levels of formaldehyde and minor changes in other smoke analytes. Toxicological studies (bacterial mutagenicity and mammalian cytoxicity tests, rat 90 days inhalation studies and bone-marrow cell micronucleus assays) found that tobacco additives did not enhance smoke toxicity. Rodent assays, however, poorly predicted carcinogenicity of tobacco smoke, and were clearly underpowered to disclose small albeit toxicologically relevant differences between test (with tobacco additives) and control (without tobacco additives) cigarettes. This literature review led to the conclusion that the impact of tobacco additives on tobacco smoke harmfulness remains unclear.

Animal models for studying female genital tract infection with Chlamydia trachomatis.

PubMed

De Clercq, Evelien; Kalmar, Isabelle; Vanrompay, Daisy

2013-09-01

Chlamydia trachomatis is a Gram-negative obligate intracellular bacterial pathogen. It is the leading cause of bacterial sexually transmitted disease in the world, with more than 100 million new cases of genital tract infections with C. trachomatis occurring each year. Animal models are indispensable for the study of C. trachomatis infections and the development and evaluation of candidate vaccines. In this paper, the most commonly used animal models to study female genital tract infections with C. trachomatis will be reviewed, namely, the mouse, guinea pig, and nonhuman primate models. Additionally, we will focus on the more recently developed pig model.

Geometrical accuracy of metallic objects produced with additive or subtractive manufacturing: A comparative in vitro study.

PubMed

Braian, Michael; Jönsson, David; Kevci, Mir; Wennerberg, Ann

2018-07-01

To evaluate the accuracy and precision of objects produced by additive manufacturing systems (AM) for use in dentistry and to compare with subtractive manufacturing systems (SM). Ten specimens of two geometrical objects were produced by five different AM machines and one SM machine. Object A mimics an inlay-shaped object, while object B imitates a four-unit bridge model. All the objects were sorted into different measurement dimensions (x, y, z), linear distances, angles and corner radius. None of the additive manufacturing or subtractive manufacturing groups presented a perfect match to the CAD file with regard to all parameters included in the present study. Considering linear measurements, the precision for subtractive manufacturing group was consistent in all axes for object A, presenting results of <0.050mm. The additive manufacturing groups had consistent precision in the x-axis and y-axis but not in the z-axis. With regard to corner radius measurements, the SM group had the best overall accuracy and precision for both objects A and B when compared to the AM groups. Within the limitations of this in vitro study, the conclusion can be made that subtractive manufacturing presented overall precision on all measurements below 0.050mm. The AM machines also presented fairly good precision, <0.150mm, on all axes except for the z-axis. Knowledge regarding accuracy and precision for different production techniques utilized in dentistry is of great clinical importance. The dental community has moved from casting to milling and additive techniques are now being implemented. Thus all these production techniques need to be tested, compared and validated. Copyright © 2018 The Academy of Dental Materials. Published by Elsevier Inc. All rights reserved.

Microbial modeling of thermal resistance of Alicyclobacillus acidoterrestris CRA7152 spores in concentrated orange juice with nisin addition

PubMed Central

Peña, Wilmer Edgard Luera; de Massaguer, Pilar Rodriguez; Teixeira, Luciano Quintão

2009-01-01

The nisin effect on thermal death of Alicyclobacillus acidoterrestris CRA 7152 spores in concentrated orange juice (64°Brix) was studied. Concentrations of 0, 50, 75 and 100 IU of nisin/ml juice, at temperatures of 92, 95, 98 and 102°C were evaluated. The quadratic polynomial model was used to analyze the effects of the factors and their interaction. Verification of surviving spores was carried out through plating in K medium (pH 3.7). The results showed that the D values without nisin addition were 25.5, 12.9, 6.1 and 2.3 min for 92, 95, 98 and 102°C respectively. With addition of nisin into the juice there was a drop of heat resistance as the concentration was increased at a same temperature. With 30, 50, 75, 100 and 150 IU/ml at 95°C, the D values were 12.34, 11.38, 10.49, 9.49 and 9.42 min respectively, showing that a decrease in the D value up to 27% can be obtained. The second order polynomial model established with r2 = 0.995 showed that the microorganism resistance was affected by the action of temperature followed by the nisin concentration. Nisin therefore is an alternative for reducing the rigor of the A. acidoterrestris CRA 7152 thermal treatment. PMID:24031405

Polylactides in additive biomanufacturing.

PubMed

Poh, Patrina S P; Chhaya, Mohit P; Wunner, Felix M; De-Juan-Pardo, Elena M; Schilling, Arndt F; Schantz, Jan-Thorsten; van Griensven, Martijn; Hutmacher, Dietmar W

2016-12-15

New advanced manufacturing technologies under the alias of additive biomanufacturing allow the design and fabrication of a range of products from pre-operative models, cutting guides and medical devices to scaffolds. The process of printing in 3 dimensions of cells, extracellular matrix (ECM) and biomaterials (bioinks, powders, etc.) to generate in vitro and/or in vivo tissue analogue structures has been termed bioprinting. To further advance in additive biomanufacturing, there are many aspects that we can learn from the wider additive manufacturing (AM) industry, which have progressed tremendously since its introduction into the manufacturing sector. First, this review gives an overview of additive manufacturing and both industry and academia efforts in addressing specific challenges in the AM technologies to drive toward AM-enabled industrial revolution. After which, considerations of poly(lactides) as a biomaterial in additive biomanufacturing are discussed. Challenges in wider additive biomanufacturing field are discussed in terms of (a) biomaterials; (b) computer-aided design, engineering and manufacturing; (c) AM and additive biomanufacturing printers hardware; and (d) system integration. Finally, the outlook for additive biomanufacturing was discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Bayesian spatiotemporal analysis of zero-inflated biological population density data by a delta-normal spatiotemporal additive model.

PubMed

Arcuti, Simona; Pollice, Alessio; Ribecco, Nunziata; D'Onghia, Gianfranco

2016-03-01

We evaluate the spatiotemporal changes in the density of a particular species of crustacean known as deep-water rose shrimp, Parapenaeus longirostris, based on biological sample data collected during trawl surveys carried out from 1995 to 2006 as part of the international project MEDITS (MEDiterranean International Trawl Surveys). As is the case for many biological variables, density data are continuous and characterized by unusually large amounts of zeros, accompanied by a skewed distribution of the remaining values. Here we analyze the normalized density data by a Bayesian delta-normal semiparametric additive model including the effects of covariates, using penalized regression with low-rank thin-plate splines for nonlinear spatial and temporal effects. Modeling the zero and nonzero values by two joint processes, as we propose in this work, allows to obtain great flexibility and easily handling of complex likelihood functions, avoiding inaccurate statistical inferences due to misclassification of the high proportion of exact zeros in the model. Bayesian model estimation is obtained by Markov chain Monte Carlo simulations, suitably specifying the complex likelihood function of the zero-inflated density data. The study highlights relevant nonlinear spatial and temporal effects and the influence of the annual Mediterranean oscillations index and of the sea surface temperature on the distribution of the deep-water rose shrimp density. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Analysis of economics of a TV broadcasting satellite for additional nationwide TV programs

NASA Technical Reports Server (NTRS)

Becker, D.; Mertens, G.; Rappold, A.; Seith, W.

1977-01-01

The influence of a TV broadcasting satellite, transmitting four additional TV networks was analyzed. It is assumed that the cost of the satellite systems will be financed by the cable TV system operators. The additional TV programs increase income by attracting additional subscribers. Two economic models were established: (1) each local network is regarded as an independent economic unit with individual fees (cost price model) and (2) all networks are part of one public cable TV company with uniform fees (uniform price model). Assumptions are made for penetration as a function of subscription rates. Main results of the study are: the installation of a TV broadcasting satellite improves the economics of CTV-networks in both models; the overall coverage achievable by the uniform price model is significantly higher than that achievable by the cost price model.

Using 3D Printing (Additive Manufacturing) to Produce Low-Cost Simulation Models for Medical Training.

PubMed

Lichtenberger, John P; Tatum, Peter S; Gada, Satyen; Wyn, Mark; Ho, Vincent B; Liacouras, Peter

2018-03-01

This work describes customized, task-specific simulation models derived from 3D printing in clinical settings and medical professional training programs. Simulation models/task trainers have an array of purposes and desired achievements for the trainee, defining that these are the first step in the production process. After this purpose is defined, computer-aided design and 3D printing (additive manufacturing) are used to create a customized anatomical model. Simulation models then undergo initial in-house testing by medical specialists followed by a larger scale beta testing. Feedback is acquired, via surveys, to validate effectiveness and to guide or determine if any future modifications and/or improvements are necessary. Numerous custom simulation models have been successfully completed with resulting task trainers designed for procedures, including removal of ocular foreign bodies, ultrasound-guided joint injections, nerve block injections, and various suturing and reconstruction procedures. These task trainers have been frequently utilized in the delivery of simulation-based training with increasing demand. 3D printing has been integral to the production of limited-quantity, low-cost simulation models across a variety of medical specialties. In general, production cost is a small fraction of a commercial, generic simulation model, if available. These simulation and training models are customized to the educational need and serve an integral role in the education of our military health professionals.

Gaussian process-based surrogate modeling framework for process planning in laser powder-bed fusion additive manufacturing of 316L stainless steel

DOE PAGES

Tapia, Gustavo; Khairallah, Saad A.; Matthews, Manyalibo J.; ...

2017-09-22

Here, Laser Powder-Bed Fusion (L-PBF) metal-based additive manufacturing (AM) is complex and not fully understood. Successful processing for one material, might not necessarily apply to a different material. This paper describes a workflow process that aims at creating a material data sheet standard that describes regimes where the process can be expected to be robust. The procedure consists of building a Gaussian process-based surrogate model of the L-PBF process that predicts melt pool depth in single-track experiments given a laser power, scan speed, and laser beam size combination. The predictions are then mapped onto a power versus scan speed diagrammore » delimiting the conduction from the keyhole melting controlled regimes. This statistical framework is shown to be robust even for cases where experimental training data might be suboptimal in quality, if appropriate physics-based filters are applied. Additionally, it is demonstrated that a high-fidelity simulation model of L-PBF can equally be successfully used for building a surrogate model, which is beneficial since simulations are getting more efficient and are more practical to study the response of different materials, than to re-tool an AM machine for new material powder.« less

Gaussian process-based surrogate modeling framework for process planning in laser powder-bed fusion additive manufacturing of 316L stainless steel

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

Tapia, Gustavo; Khairallah, Saad A.; Matthews, Manyalibo J.

Here, Laser Powder-Bed Fusion (L-PBF) metal-based additive manufacturing (AM) is complex and not fully understood. Successful processing for one material, might not necessarily apply to a different material. This paper describes a workflow process that aims at creating a material data sheet standard that describes regimes where the process can be expected to be robust. The procedure consists of building a Gaussian process-based surrogate model of the L-PBF process that predicts melt pool depth in single-track experiments given a laser power, scan speed, and laser beam size combination. The predictions are then mapped onto a power versus scan speed diagrammore » delimiting the conduction from the keyhole melting controlled regimes. This statistical framework is shown to be robust even for cases where experimental training data might be suboptimal in quality, if appropriate physics-based filters are applied. Additionally, it is demonstrated that a high-fidelity simulation model of L-PBF can equally be successfully used for building a surrogate model, which is beneficial since simulations are getting more efficient and are more practical to study the response of different materials, than to re-tool an AM machine for new material powder.« less

Effect of Hydrogen Addition on Methane HCCI Engine Ignition Timing and Emissions Using a Multi-zone Model

NASA Astrophysics Data System (ADS)

Wang, Zi-han; Wang, Chun-mei; Tang, Hua-xin; Zuo, Cheng-ji; Xu, Hong-ming

2009-06-01

Ignition timing control is of great importance in homogeneous charge compression ignition engines. The effect of hydrogen addition on methane combustion was investigated using a CHEMKIN multi-zone model. Results show that hydrogen addition advances ignition timing and enhances peak pressure and temperature. A brief analysis of chemical kinetics of methane blending hydrogen is also performed in order to investigate the scope of its application, and the analysis suggests that OH radical plays an important role in the oxidation. Hydrogen addition increases NOx while decreasing HC and CO emissions. Exhaust gas recirculation (EGR) also advances ignition timing; however, its effects on emissions are generally the opposite. By adjusting the hydrogen addition and EGR rate, the ignition timing can be regulated with a low emission level. Investigation into zones suggests that NOx is mostly formed in core zones while HC and CO mostly originate in the crevice and the quench layer.

Color Addition and Subtraction Apps

ERIC Educational Resources Information Center

Ruiz, Frances; Ruiz, Michael J.

2015-01-01

Color addition and subtraction apps in HTML5 have been developed for students as an online hands-on experience so that they can more easily master principles introduced through traditional classroom demonstrations. The evolution of the additive RGB color model is traced through the early IBM color adapters so that students can proceed step by step…

Mechanisms and modeling of the effects of additives on the nitrogen oxides emission

NASA Technical Reports Server (NTRS)

Kundu, Krishna P.; Nguyen, Hung Lee; Kang, M. Paul

1991-01-01

A theoretical study on the emission of the oxides of nitrogen in the combustion of hydrocarbons is presented. The current understanding of the mechanisms and the rate parameters for gas phase reactions were used to calculate the NO(x) emission. The possible effects of different chemical species on thermal NO(x), on a long time scale were discussed. The mixing of these additives at various stages of combustion were considered and NO(x) concentrations were calculated; effects of temperatures were also considered. The chemicals such as hydrocarbons, H2, CH3OH, NH3, and other nitrogen species were chosen as additives in this discussion. Results of these calculations can be used to evaluate the effects of these additives on the NO(x) emission in the industrial combustion system.

Spectra-temporal patterns underlying mental addition: an ERP and ERD/ERS study.

PubMed

Ku, Yixuan; Hong, Bo; Gao, Xiaorong; Gao, Shangkai

2010-03-12

Functional neuroimaging data have shown that mental calculation involves fronto-parietal areas that are composed of different subsystems shared with other cognitive functions such as working memory and language. Event-related potential (ERP) analysis has also indicated sequential information changes during the calculation process. However, little is known about the dynamic properties of oscillatory networks in this process. In the present study, we applied both ERP and event-related (de-)synchronization (ERS/ERD) analyses to EEG data recorded from normal human subjects performing tasks for sequential visual/auditory mental addition. Results in the study indicate that the late positive components (LPCs) can be decomposed into two separate parts. The earlier element LPC1 (around 360ms) reflects the computing attribute and is more prominent in calculation tasks. The later element LPC2 (around 590ms) indicates an effect of number size and appears larger only in a more complex 2-digit addition task. The theta ERS and alpha ERD show modality-independent frontal and parietal differential patterns between the mental addition and control groups, and discrepancies are noted in the beta ERD between the 2-digit and 1-digit mental addition groups. The 2-digit addition (both visual and auditory) results in similar beta ERD patterns to the auditory control, which may indicate a reliance on auditory-related resources in mental arithmetic, especially with increasing task difficulty. These results coincide with the theory of simple calculation relying on the visuospatial process and complex calculation depending on the phonological process. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Unraveling additive from nonadditive effects using genomic relationship matrices.

PubMed

Muñoz, Patricio R; Resende, Marcio F R; Gezan, Salvador A; Resende, Marcos Deon Vilela; de Los Campos, Gustavo; Kirst, Matias; Huber, Dudley; Peter, Gary F

2014-12-01

The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies. Copyright © 2014 by the Genetics Society of America.

From path models to commands during additive printing of large-scale architectural designs

NASA Astrophysics Data System (ADS)

Chepchurov, M. S.; Zhukov, E. M.; Yakovlev, E. A.; Matveykin, V. G.

2018-05-01

The article considers the problem of automation of the formation of large complex parts, products and structures, especially for unique or small-batch objects produced by a method of additive technology [1]. Results of scientific research in search for the optimal design of a robotic complex, its modes of operation (work), structure of its control helped to impose the technical requirements on the technological process for manufacturing and design installation of the robotic complex. Research on virtual models of the robotic complexes allowed defining the main directions of design improvements and the main goal (purpose) of testing of the the manufactured prototype: checking the positioning accuracy of the working part.

A modeling study of marine boundary layer clouds

NASA Technical Reports Server (NTRS)

Wang, Shouping; Fitzjarrald, Daniel E.

1993-01-01

Marine boundary layer (MBL) clouds are important components of the earth's climate system. These clouds drastically reduce the amount of solar radiation absorbed by the earth, but have little effect on the emitted infrared radiation on top of the atmosphere. In addition, these clouds are intimately involved in regulating boundary layer turbulent fluxes. For these reasons, it is important that general circulation models used for climate studies must realistically simulate the global distribution of the MBL. While the importance of these cloud systems is well recognized, many physical processes involved in these clouds are poorly understood and their representation in large-scale models remains an unresolved problem. The present research aims at the development and improvement of the parameterization of these cloud systems and an understanding of physical processes involved. This goal is addressed in two ways. One is to use regional modeling approach to validate and evaluate two-layer marine boundary layer models using satellite and ground-truth observations; the other is to combine this simple model with a high-order turbulence closure model to study the transition processes from stratocumulus to shallow cumulus clouds. Progress made in this effort is presented.

Covariate adjustment of event histories estimated from Markov chains: the additive approach.

PubMed

Aalen, O O; Borgan, O; Fekjaer, H

2001-12-01

Markov chain models are frequently used for studying event histories that include transitions between several states. An empirical transition matrix for nonhomogeneous Markov chains has previously been developed, including a detailed statistical theory based on counting processes and martingales. In this article, we show how to estimate transition probabilities dependent on covariates. This technique may, e.g., be used for making estimates of individual prognosis in epidemiological or clinical studies. The covariates are included through nonparametric additive models on the transition intensities of the Markov chain. The additive model allows for estimation of covariate-dependent transition intensities, and again a detailed theory exists based on counting processes. The martingale setting now allows for a very natural combination of the empirical transition matrix and the additive model, resulting in estimates that can be expressed as stochastic integrals, and hence their properties are easily evaluated. Two medical examples will be given. In the first example, we study how the lung cancer mortality of uranium miners depends on smoking and radon exposure. In the second example, we study how the probability of being in response depends on patient group and prophylactic treatment for leukemia patients who have had a bone marrow transplantation. A program in R and S-PLUS that can carry out the analyses described here has been developed and is freely available on the Internet.

Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis.

PubMed

Enden, T; Resch, S; White, C; Wik, H S; Kløw, N E; Sandset, P M

2013-06-01

Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64,709 for additional CDT and $51,866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20,429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55,000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50,000/QALY gained. Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. © 2013 International Society on Thrombosis and Haemostasis.

Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis

PubMed Central

ENDEN, T.; RESCH, S.; WHITE, C.; WIK, H. S.; KLØW, N. E.; SANDSET, P. M.

2013-01-01

Summary Background Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). Objectives To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Methods Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). Results In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64 709 for additional CDT and $51 866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20 429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55 000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50 000/QALY gained. Conclusions Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. PMID:23452204

Microwave Sanitization of Color Additives Used in Cosmetics: Feasibility Study

PubMed Central

Jasnow, S. B.; Smith, J. L.

1975-01-01

Microwave exposure has been explored as a method of microbiologically sanitizing color additives used in cosmetic products. Selected microbiologically unacceptable cosmetic color additives, D&C red no. 7 Ca lake (certified synthetic organic color), carmine (natural organic color not subject to certification), and chromium hydroxide green (inorganic color not subject to certification), were submitted to microwave exposure. Gram-negative bacteria were eliminated, as verified by enrichment procedures, and levels of gram-positive bacteria were reduced. Generally, analytical and dermal safety studies indicated no significant alterations in physical, chemical, and toxicological properties of the colors. Sanitization was also successfully performed on other colors (D&C red no. 9 Ba lake, D&C red no. 12 Ba lake, D&C green no. 5, and FD&C red no. 4); initial physical and chemical tests were satisfactory. Results indicated that this method of sanitization is feasible and warrants further investigation. PMID:1164010

Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks.

PubMed

Xue, Hongqi; Wu, Shuang; Wu, Yichao; Ramirez Idarraga, Juan C; Wu, Hulin

2018-05-02

Mechanism-driven low-dimensional ordinary differential equation (ODE) models are often used to model viral dynamics at cellular levels and epidemics of infectious diseases. However, low-dimensional mechanism-based ODE models are limited for modeling infectious diseases at molecular levels such as transcriptomic or proteomic levels, which is critical to understand pathogenesis of diseases. Although linear ODE models have been proposed for gene regulatory networks (GRNs), nonlinear regulations are common in GRNs. The reconstruction of large-scale nonlinear networks from time-course gene expression data remains an unresolved issue. Here, we use high-dimensional nonlinear additive ODEs to model GRNs and propose a 4-step procedure to efficiently perform variable selection for nonlinear ODEs. To tackle the challenge of high dimensionality, we couple the 2-stage smoothing-based estimation method for ODEs and a nonlinear independence screening method to perform variable selection for the nonlinear ODE models. We have shown that our method possesses the sure screening property and it can handle problems with non-polynomial dimensionality. Numerical performance of the proposed method is illustrated with simulated data and a real data example for identifying the dynamic GRN of Saccharomyces cerevisiae. Copyright © 2018 John Wiley & Sons, Ltd.

Quantification of Treatment Effect Modification on Both an Additive and Multiplicative Scale

PubMed Central

Girerd, Nicolas; Rabilloud, Muriel; Pibarot, Philippe; Mathieu, Patrick; Roy, Pascal

2016-01-01

Background In both observational and randomized studies, associations with overall survival are by and large assessed on a multiplicative scale using the Cox model. However, clinicians and clinical researchers have an ardent interest in assessing absolute benefit associated with treatments. In older patients, some studies have reported lower relative treatment effect, which might translate into similar or even greater absolute treatment effect given their high baseline hazard for clinical events. Methods The effect of treatment and the effect modification of treatment were respectively assessed using a multiplicative and an additive hazard model in an analysis adjusted for propensity score in the context of coronary surgery. Results The multiplicative model yielded a lower relative hazard reduction with bilateral internal thoracic artery grafting in older patients (Hazard ratio for interaction/year = 1.03, 95%CI: 1.00 to 1.06, p = 0.05) whereas the additive model reported a similar absolute hazard reduction with increasing age (Delta for interaction/year = 0.10, 95%CI: -0.27 to 0.46, p = 0.61). The number needed to treat derived from the propensity score-adjusted multiplicative model was remarkably similar at the end of the follow-up in patients aged < = 60 and in patients >70. Conclusions The present example demonstrates that a lower treatment effect in older patients on a relative scale can conversely translate into a similar treatment effect on an additive scale due to large baseline hazard differences. Importantly, absolute risk reduction, either crude or adjusted, can be calculated from multiplicative survival models. We advocate for a wider use of the absolute scale, especially using additive hazard models, to assess treatment effect and treatment effect modification. PMID:27045168

Design and modeling of an additive manufactured thin shell for x-ray astronomy

NASA Astrophysics Data System (ADS)

Feldman, Charlotte; Atkins, Carolyn; Brooks, David; Watson, Stephen; Cochrane, William; Roulet, Melanie; Willingale, Richard; Doel, Peter

2017-09-01

Future X-ray astronomy missions require light-weight thin shells to provide large collecting areas within the weight limits of launch vehicles, whilst still delivering angular resolutions close to that of Chandra (0.5 arc seconds). Additive manufacturing (AM), also known as 3D printing, is a well-established technology with the ability to construct or `print' intricate support structures, which can be both integral and light-weight, and is therefore a candidate technique for producing shells for space-based X-ray telescopes. The work described here is a feasibility study into this technology for precision X-ray optics for astronomy and has been sponsored by the UK Space Agency's National Space Technology Programme. The goal of the project is to use a series of test samples to trial different materials and processes with the aim of developing a viable path for the production of an X-ray reflecting prototype for astronomical applications. The initial design of an AM prototype X-ray shell is presented with ray-trace modelling and analysis of the X-ray performance. The polishing process may cause print-through from the light-weight support structure on to the reflecting surface. Investigations in to the effect of the print-through on the X-ray performance of the shell are also presented.

Additive-dominance genetic model analyses for late-maturity alpha-amylase activity in a bread wheat factorial crossing population.

PubMed

Rasul, Golam; Glover, Karl D; Krishnan, Padmanaban G; Wu, Jixiang; Berzonsky, William A; Ibrahim, Amir M H

2015-12-01

Elevated level of late maturity α-amylase activity (LMAA) can result in low falling number scores, reduced grain quality, and downgrade of wheat (Triticum aestivum L.) class. A mating population was developed by crossing parents with different levels of LMAA. The F2 and F3 hybrids and their parents were evaluated for LMAA, and data were analyzed using the R software package 'qgtools' integrated with an additive-dominance genetic model and a mixed linear model approach. Simulated results showed high testing powers for additive and additive × environment variances, and comparatively low powers for dominance and dominance × environment variances. All variance components and their proportions to the phenotypic variance for the parents and hybrids were significant except for the dominance × environment variance. The estimated narrow-sense heritability and broad-sense heritability for LMAA were 14 and 54%, respectively. High significant negative additive effects for parents suggest that spring wheat cultivars 'Lancer' and 'Chester' can serve as good general combiners, and that 'Kinsman' and 'Seri-82' had negative specific combining ability in some hybrids despite of their own significant positive additive effects, suggesting they can be used as parents to reduce LMAA levels. Seri-82 showed very good general combining ability effect when used as a male parent, indicating the importance of reciprocal effects. High significant negative dominance effects and high-parent heterosis for hybrids demonstrated that the specific hybrid combinations; Chester × Kinsman, 'Lerma52' × Lancer, Lerma52 × 'LoSprout' and 'Janz' × Seri-82 could be generated to produce cultivars with significantly reduced LMAA level.

Color Addition and Subtraction Apps

NASA Astrophysics Data System (ADS)

Ruiz, Frances; Ruiz, Michael J.

2015-10-01

Color addition and subtraction apps in HTML5 have been developed for students as an online hands-on experience so that they can more easily master principles introduced through traditional classroom demonstrations. The evolution of the additive RGB color model is traced through the early IBM color adapters so that students can proceed step by step in understanding mathematical representations of RGB color. Finally, color addition and subtraction are presented for the X11 colors from web design to illustrate yet another real-life application of color mixing.

Effects of Rhenium Addition on the Temporal Evolution of the Nanostructure and Chemistry of a Model Ni-Cr-Al Superalloy. 2; Analysis of the Coarsening Behavior

NASA Technical Reports Server (NTRS)

Yoon, Kevin E.; Noebe, Ronald D.; Seidman, David N.

2007-01-01

The temporal evolution of the nanostructure and chemistry of a model Ni-8.5 at.% Cr-10 at.% Al alloy with the addition of 2 at.% Re was studied using transmission electron microscopy and atom-probe tomography in order to measure the number density and mean radius of the y' (LIZ) precipitates and the chemistry of the y'-precipitates and the y (fcc)-matrix. In this article, the coarsening behavior of the y'-precipitates is discussed in detail and compared with the Umantsev-Olson model for multi-component alloys. In addition, the experimental results are evaluated with PrecipiCalc(TradeMark) simulations. The results show that the diffusivities of the solute elements play a major role in the coarsening behavior of the y'-precipitates and that the addition of Re retards the coarsening kinetics and stabilizes the spheroidal morphology of the precipitates by reducing the interfacial energy.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Design and additive manufacture for flow chemistry.

PubMed

Capel, Andrew J; Edmondson, Steve; Christie, Steven D R; Goodridge, Ruth D; Bibb, Richard J; Thurstans, Matthew

2013-12-07

We review the use of additive manufacturing (AM) as a novel manufacturing technique for the production of milli-scale reactor systems. Five well-developed additive manufacturing techniques: stereolithography (SL), multi-jet modelling (MJM), selective laser melting (SLM), laser sintering (LS) and fused deposition modelling (FDM) were used to manufacture a number of miniaturised reactors which were tested using a range of organic and inorganic reactions.

Additive Manufacturing of Biomaterials, Tissues, and Organs.

PubMed

Zadpoor, Amir A; Malda, Jos

2017-01-01

The introduction of additive manufacturing (AM), often referred to as three-dimensional (3D) printing, has initiated what some believe to be a manufacturing revolution, and has expedited the development of the field of biofabrication. Moreover, recent advances in AM have facilitated further development of patient-specific healthcare solutions. Customization of many healthcare products and services, such as implants, drug delivery devices, medical instruments, prosthetics, and in vitro models, would have been extremely challenging-if not impossible-without AM technologies. The current special issue of the Annals of Biomedical Engineering presents the latest trends in application of AM techniques to healthcare-related areas of research. As a prelude to this special issue, we review here the most important areas of biomedical research and clinical practice that have benefited from recent developments in additive manufacturing techniques. This editorial, therefore, aims to sketch the research landscape within which the other contributions of the special issue can be better understood and positioned. In what follows, we briefly review the application of additive manufacturing techniques in studies addressing biomaterials, (re)generation of tissues and organs, disease models, drug delivery systems, implants, medical instruments, prosthetics, orthotics, and AM objects used for medical visualization and communication.

Evaluating Drugs and Food Additives for Public Use: A Case Studies Approach.

ERIC Educational Resources Information Center

Merritt, Sheridan V.

1980-01-01

Described is a case study used in an introductory college biology course that provides a basis for generating debate on an issue concerning the regulation of controversial food additives and prescription drugs. The case study contained within this article deals with drug screening, specifically with information related to thalidomide. (CS)

Model assessment of additional contamination of water bodies as a result of wildfires in the Chernobyl exclusion zone.

PubMed

Bondar, Yu I; Navumau, A D; Nikitin, A N; Brown, J; Dowdall, M

2014-12-01

Forest fires and wild fires are recognized as a possible cause of resuspension and redistribution of radioactive substances when occurring on lands contaminated with such materials, and as such are a matter of concern within the regions of Belarus and the Ukraine which were contaminated by the Chernobyl accident in 1986. Modelling the effects of such fires on radioactive contaminants is a complex matter given the number of variables involved. In this paper, a probabilistic model was developed using empirical data drawn from the Polessie State Radiation-Ecological Reserve (PSRER), Belarus, and the Maximum Entropy Method. Using the model, it was possible to derive estimates of the contribution of fire events to overall variability in the levels of (137)Cs and (239,240)Pu in ground air as well as estimates of the deposition of these radionuclides to specific water bodies within the contaminated areas of Belarus. Results indicate that fire events are potentially significant redistributors of radioactive contaminants within the study area and may result in additional contamination being introduced to water bodies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Addition of Autologous Mesenchymal Stem Cells to Whole Blood for Bio-Enhanced ACL Repair has No Benefit in the Porcine Model

PubMed Central

Proffen, Benedikt L.; Vavken, Patrick; Haslauer, Carla M.; Fleming, Braden C.; Harris, Chad E.; Machan, Jason T.; Murray, Martha M.

2015-01-01

Background Co-culture of mesenchymal stem cells (MSCs) from the retropatellar fat pad and peripheral blood has been shown to stimulate anterior cruciate ligament (ACL) fibroblast proliferation and collagen production in vitro. Current techniques of bio-enhanced ACL repair in animal studies involve adding a biologic scaffold, in this case an extracellular matrix based scaffold saturated with autologous whole blood, to a simple suture repair of the ligament. Whether the enrichment of whole blood with MSCs would further improve the in vivo results of bio-enhanced ACL repair was investigated. Hypothesis/Purpose The hypothesis was that the addition of MSCs derived from adipose tissue or peripheral blood to the blood-extracellular matrix composite, which is used in bio-enhanced ACL repair to stimulate healing, would improve the biomechanical properties of a bio-enhanced ACL repair after 15 weeks of healing. Study Design Controlled laboratory study. Methods Twenty-four adolescent Yucatan mini-pigs underwent ACL transection followed by: 1) bio-enhanced ACL repair, 2) bio-enhanced ACL repair with the addition of autologous adipose-derived MSCs and 3) bio-enhanced ACL repair with the addition of autologous peripheral blood derived MSCs. After fifteen weeks of healing, structural properties of the ACL (yield & failure load, linear stiffness) were measured. Cell and vascular density were measured in the repaired ACL via histology, and its tissue structure was qualitatively evaluated using the Advanced Ligament Maturity Index. Results After fifteen weeks of healing, there were no significant improvements in the biomechanical or histological properties with the addition of adipose-derived MSCs. The only significant change with the addition of peripheral blood MSCs was an increase in knee anteroposterior (AP) laxity when measured at 30 degrees of flexion. Conclusions These findings suggest that the addition of adipose or peripheral blood MSCs to whole blood prior to saturation of

Robot-based additive manufacturing for flexible die-modelling in incremental sheet forming

NASA Astrophysics Data System (ADS)

Rieger, Michael; Störkle, Denis Daniel; Thyssen, Lars; Kuhlenkötter, Bernd

2017-10-01

The paper describes the application concept of additive manufactured dies to support the robot-based incremental sheet metal forming process (`Roboforming') for the production of sheet metal components in small batch sizes. Compared to the dieless kinematic-based generation of a shape by means of two cooperating industrial robots, the supporting robot models a die on the back of the metal sheet by using the robot-based fused layer manufacturing process (FLM). This tool chain is software-defined and preserves the high geometrical form flexibility of Roboforming while flexibly generating support structures adapted to the final part's geometry. Test series serve to confirm the feasibility of the concept by investigating the process challenges of the adhesion to the sheet surface and the general stability as well as the influence on the geometric accuracy compared to the well-known forming strategies.

Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials.

PubMed

Dias, Kaio Olímpio Das Graças; Gezan, Salvador Alejandro; Guimarães, Claudia Teixeira; Nazarian, Alireza; da Costa E Silva, Luciano; Parentoni, Sidney Netto; de Oliveira Guimarães, Paulo Evaristo; de Oliveira Anoni, Carina; Pádua, José Maria Villela; de Oliveira Pinto, Marcos; Noda, Roberto Willians; Ribeiro, Carlos Alexandre Gomes; de Magalhães, Jurandir Vieira; Garcia, Antonio Augusto Franco; de Souza, João Cândido; Guimarães, Lauro José Moreira; Pastina, Maria Marta

2018-07-01

Breeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multi-environment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids' genotypes were inferred based on their parents' genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS and using CV1, the AD model doubled the predictive accuracy in comparison to the A model. Through CV2, GS models benefit from borrowing information of correlated trials, resulting in an increase of 40% and 9% in the predictive accuracy of GY under WS for A and AD models, respectively. These results highlight the importance of multi-environment trial analyses using GS models that incorporate additive and dominance effects for genomic predictions of GY under drought in maize single

Tribological study on rapeseed oil with nano-additives in close contact sliding situation

NASA Astrophysics Data System (ADS)

Gupta, Rajeev Nayan; Harsha, A. P.; Singh, Sagar

2018-02-01

The present work deals with the tribological evaluation of three types of nano-additives, i.e., copper oxide (CuO; ≈ 151.2 nm), cerium oxide (CeO2; ≈ 80 nm) and polytetrafluoroethylene (PTFE; ≈ 90.4 nm) with rapeseed oil under steel-steel sliding contacts. The nano-additives concentrations in the base oil were 0.1, 0.25 and 0.5% w/v for the lubricant formulation. Further, the rapeseed oil was also epoxidized by a chemical method and the tribological behavior was compared with the base oil (unmodified oil) at similar nano-additives concentrations. The ASTM standards were followed for the study of wear preventive and extreme-pressure analysis of nanolubricants, and it was carried out using four-ball tester. In the antiwear test, CeO2 and PTFE nano-additives have shown the significant reduction in the wear scar diameter at the concentration of 0.1% w/v. In the extreme-pressure test, 0.5% w/v concentration was optimum for oxide nanoparticles; however, PTFE nanoparticles did not show positive effect with both the base oils. Different characterization techniques were employed to confirm the oil modification and for the study of the worn surfaces.

Resource Tracking Model Updates and Trade Studies

NASA Technical Reports Server (NTRS)

Chambliss, Joe; Stambaugh, Imelda; Moore, Michael

2016-01-01

The Resource Tracking Model has been updated to capture system manager and project manager inputs. Both the Trick/General Use Nodal Network Solver Resource Tracking Model (RTM) simulator and the RTM mass balance spreadsheet have been revised to address inputs from system managers and to refine the way mass balance is illustrated. The revisions to the RTM included the addition of a Plasma Pyrolysis Assembly (PPA) to recover hydrogen from Sabatier Reactor methane, which was vented in the prior version of the RTM. The effect of the PPA on the overall balance of resources in an exploration vehicle is illustrated in the increased recycle of vehicle oxygen. Case studies have been run to show the relative effect of performance changes on vehicle resources.

Addition of autologous mesenchymal stem cells to whole blood for bioenhanced ACL repair has no benefit in the porcine model.

PubMed

Proffen, Benedikt L; Vavken, Patrick; Haslauer, Carla M; Fleming, Braden C; Harris, Chad E; Machan, Jason T; Murray, Martha M

2015-02-01

Coculture of mesenchymal stem cells (MSCs) from the retropatellar fat pad and peripheral blood has been shown to stimulate anterior cruciate ligament (ACL) fibroblast proliferation and collagen production in vitro. Current techniques of bioenhanced ACL repair in animal studies involve adding a biologic scaffold, in this case an extracellular matrix-based scaffold saturated with autologous whole blood, to a simple suture repair of the ligament. Whether the enrichment of whole blood with MSCs would further improve the in vivo results of bioenhanced ACL repair was investigated. The addition of MSCs derived from adipose tissue or peripheral blood to the blood-extracellular matrix composite, which is used in bioenhanced ACL repair to stimulate healing, would improve the biomechanical properties of a bioenhanced ACL repair after 15 weeks of healing. Controlled laboratory study. Twenty-four adolescent Yucatan mini-pigs underwent ACL transection followed by (1) bioenhanced ACL repair, (2) bioenhanced ACL repair with the addition of autologous adipose-derived MSCs, and (3) bioenhanced ACL repair with the addition of autologous peripheral blood derived MSCs. After 15 weeks of healing, the structural properties of the ACL (yield load, failure load, and linear stiffness) were measured. Cell and vascular density were measured in the repaired ACL via histology, and its tissue structure was qualitatively evaluated using the advanced Ligament Maturity Index. After 15 weeks of healing, there were no significant improvements in the biomechanical or histological properties with the addition of adipose-derived MSCs. The only significant change with the addition of peripheral blood MSCs was an increase in knee anteroposterior laxity when measured at 30° of flexion. These findings suggest that the addition of adipose or peripheral blood MSCs to whole blood before saturation of an extracellular matrix carrier with the blood did not improve the functional results of bioenhanced ACL

Conservative Exposure Predictions for Rapid Risk Assessment of Phase-Separated Additives in Medical Device Polymers.

PubMed

Chandrasekar, Vaishnavi; Janes, Dustin W; Saylor, David M; Hood, Alan; Bajaj, Akhil; Duncan, Timothy V; Zheng, Jiwen; Isayeva, Irada S; Forrey, Christopher; Casey, Brendan J

2018-01-01

A novel approach for rapid risk assessment of targeted leachables in medical device polymers is proposed and validated. Risk evaluation involves understanding the potential of these additives to migrate out of the polymer, and comparing their exposure to a toxicological threshold value. In this study, we propose that a simple diffusive transport model can be used to provide conservative exposure estimates for phase separated color additives in device polymers. This model has been illustrated using a representative phthalocyanine color additive (manganese phthalocyanine, MnPC) and polymer (PEBAX 2533) system. Sorption experiments of MnPC into PEBAX were conducted in order to experimentally determine the diffusion coefficient, D = (1.6 ± 0.5) × 10 -11  cm 2 /s, and matrix solubility limit, C s  = 0.089 wt.%, and model predicted exposure values were validated by extraction experiments. Exposure values for the color additive were compared to a toxicological threshold for a sample risk assessment. Results from this study indicate that a diffusion model-based approach to predict exposure has considerable potential for use as a rapid, screening-level tool to assess the risk of color additives and other small molecule additives in medical device polymers.

Additional Research Needs to Support the GENII Biosphere Models

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

Napier, Bruce A.; Snyder, Sandra F.; Arimescu, Carmen

In the course of evaluating the current parameter needs for the GENII Version 2 code (Snyder et al. 2013), areas of possible improvement for both the data and the underlying models have been identified. As the data review was implemented, PNNL staff identified areas where the models can be improved both to accommodate the locally significant pathways identified and also to incorporate newer models. The areas are general data needs for the existing models and improved formulations for the pathway models.

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.

Learning a Language and Studying Content in an Additional Language: Student Opinions

ERIC Educational Resources Information Center

Ger, Ugur; Bahar, Mustafa

2018-01-01

This study aims to understand the opinions of middle school and high school students about language learning and studying other content in an additional language in the school settings where English is used as the medium of instruction to teach more than 50% of the curriculum. For this end, 261 students from three different schools were…

Genotypic variability-based genome-wide association study identifies non-additive loci HLA-C and IL12B for psoriasis.

PubMed

Wei, Wen-Hua; Massey, Jonathan; Worthington, Jane; Barton, Anne; Warren, Richard B

2018-03-01

Genome-wide association studies (GWASs) have identified a number of loci for psoriasis but largely ignored non-additive effects. We report a genotypic variability-based GWAS (vGWAS) that can prioritize non-additive loci without requiring prior knowledge of interaction types or interacting factors in two steps, using a mixed model to partition dichotomous phenotypes into an additive component and non-additive environmental residuals on the liability scale and then the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups genome widely. The vGWAS identified two genome-wide significant (P < 5.0e-08) non-additive loci HLA-C and IL12B that were also genome-wide significant in an accompanying GWAS in the discovery cohort. Both loci were statistically replicated in vGWAS of an independent cohort with a small sample size. HLA-C and IL12B were reported in moderate gene-gene and/or gene-environment interactions in several occasions. We found a moderate interaction with age-of-onset of psoriasis, which was replicated indirectly. The vGWAS also revealed five suggestive loci (P < 6.76e-05) including FUT2 that was associated with psoriasis with environmental aspects triggered by virus infection and/or metabolic factors. Replication and functional investigation are needed to validate the suggestive vGWAS loci.

The influence of inquiry learning model on additives theme with ethnoscience content to cultural awareness of students

NASA Astrophysics Data System (ADS)

Sudarmin, S.; Selia, E.; Taufiq, M.

2018-03-01

The purpose of this research is to determine the influence of inquiry learning model on additives theme with ethnoscience content to cultural awareness of students and how the students’ responses to learning. The method applied in this research is a quasi-experimental with non-equivalent control group design. The sampling technique applied in this research is the technique of random sampling. The samples were eight grade students of one of junior high schools in Semarang. The results of this research were (1) thestudents’ cultural awareness of the experiment class is better than the control class (2) inquiry learning model with ethnoscience content strongly influencing the cultural awareness of students by 78% and (3) students gave positive responses to inquiry learning model with ethnoscience content. The conclusions of this research are inquiry-learning model with ethnoscience content has positive influence on students’ cultural awareness.

ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices.

PubMed

Wilderjans, Tom F; Ceulemans, Eva; Van Mechelen, Iven; Depril, Dirk

2011-03-01

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

PubMed Central

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

PubMed

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we

Additive Manufacturing of Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Van Humbeeck, Jan

2018-04-01

Selective Laser Melting (SLM) is an additive manufacturing production process, also called 3D printing, in which functional, complex parts are produced by selectively melting patterns in consecutive layers of powder with a laser beam. The pattern the laser beam is following is controlled by software that calculates the pattern by slicing a 3D CAD model of the part to be constructed. Apart from SLM, also other additive manufacturing techniques such as EBM (Electron Beam Melting), FDM (Fused Deposition Modelling), WAAM (Wire Arc Additive Manufacturing), LENS (Laser Engineered Net Shaping such as Laser Cladding) and binder jetting allow to construct complete parts layer upon layer. But since more experience of AM of shape memory alloys is collected by SLM, this paper will overview the potentials, limits and problems of producing NiTi parts by SLM.

Teaching Facts of Addition to Brazilian Children with Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Costa, Adriana Corrêa; Rohde, Luis Augusto; Dorneles, Beatriz Vargas

2015-01-01

Storage and/or automatic retrieval of the basic facts of addition from the long-term memory seems to be impaired in children with ADHD presenting arithmetical difficulties. The present study was carried out to evaluate the effectiveness of an educational intervention model designed to teach basic facts of addition as a means of advancing from…

Accelerated cure of phenol-formaldehyde resins : studies with model compounds

Treesearch

Anthony H. Conner; Linda F. Lorenz; Kolby C. Hirth

2002-01-01

2-Hydroxymethylphenol (2-HMP) and 4-hydroxymethylphenol (4-HMP) were used as model compounds to study the reactions that occur during cure of phenol-formaldehyde (PF) resin to which cure accelerators (ethyl formate, propylene carbonate, g-butyrolactone, and triacetin) have been added. The addition of cure accelerators significantly increased the rate of condensation...

Effectiveness of the Touch Math Technique in Teaching Basic Addition to Children with Autism

ERIC Educational Resources Information Center

Yikmis, Ahmet

2016-01-01

This study aims to reveal whether the touch math technique is effective in teaching basic addition to children with autism. The dependent variable of this study is the children's skills to solve addition problems correctly, whereas teaching with the touch math technique is the independent variable. Among the single-subject research models, a…

Additive Manufacturing (AM) in Expeditionary Operations: Current Needs, Technical Challenges, and Opportunities

DTIC Science & Technology

2016-06-01

site customization of existing models. The author performed an empirical study centered around a survey of United States Marine Corps (USMC) and United...recommends that more studies be performed to determine the best way forward for AM within the USMC and USN. 14. SUBJECT TERMS 3D printing, additive...customization of existing models. The author performed an em- pirical study centered around a survey of United States Marine Corps (USMC) and United

Real-time slicing algorithm for Stereolithography (STL) CAD model applied in additive manufacturing industry

NASA Astrophysics Data System (ADS)

Adnan, F. A.; Romlay, F. R. M.; Shafiq, M.

2018-04-01

Owing to the advent of the industrial revolution 4.0, the need for further evaluating processes applied in the additive manufacturing application particularly the computational process for slicing is non-trivial. This paper evaluates a real-time slicing algorithm for slicing an STL formatted computer-aided design (CAD). A line-plane intersection equation was applied to perform the slicing procedure at any given height. The application of this algorithm has found to provide a better computational time regardless the number of facet in the STL model. The performance of this algorithm is evaluated by comparing the results of the computational time for different geometry.

Gut Health of Pigs: Challenge Models and Response Criteria with a Critical Analysis of the Effectiveness of Selected Feed Additives - A Review.

PubMed

Adewole, D I; Kim, I H; Nyachoti, C M

2016-07-01

The gut is the largest organ that helps with the immune function. Gut health, especially in young pigs has a significant benefit to health and performance. In an attempt to maintain and enhance intestinal health in pigs and improve productivity in the absence of in-feed antibiotics, researchers have evaluated a wide range of feed additives. Some of these additives such as zinc oxide, copper sulphate, egg yolk antibodies, mannan-oligosaccharides and spray dried porcine plasma and their effectiveness are discussed in this review. One approach to evaluate the effectiveness of these additives in vivo is to use an appropriate disease challenge model. Over the years, researchers have used a number of challenge models which include the use of specific strains of enterotoxigenic Escherichia coli, bacteria lipopolysaccharide challenge, oral challenge with Salmonella enteric serotype Typhimurium, sanitation challenge, and Lawsonia intercellularis challenge. These challenge models together with the criteria used to evaluate the responses of the animals to them are also discussed in this review.

A feasibility study regarding the addition of a fifth control to a rotorcraft in-flight simulator

NASA Technical Reports Server (NTRS)

Turner, Simon; Andrisani, Dominick, II

1992-01-01

The addition of a large movable horizontal tail surface to the control system of a rotorcraft in-flight simulator being developed from a Sikorsky UH-60A Black Hawk Helicopter is evaluated. The capabilities of the control surface as a trim control and as an active control are explored. The helicopter dynamics are modeled using the Generic Helicopter simulation program developed by Sikorsky Aircraft. The effect of the horizontal tail on the helicopter trim envelope is examined by plotting trim maps of the aircraft attitude and controls as a function of the flight speed and horizontal tail incidence. The control power of the tail surface relative to that of the other controls is examined by comparing control derivatives extracted from the simulation program over the flight speed envelope. The horizontal tail's contribution as an active control is evaluated using an explicit model following control synthesis involving a linear model of the helicopter in steady, level flight at a flight speed of eighty knots. The horizontal tail is found to provide additional control flexibility in the longitudinal axis. As a trim control, it provides effective control of the trim pitch attitude at mid to high forward speeds. As an active control, the horizontal tail provides useful pitching moment generating capabilities at mid to high forward speeds.

Non-additivity of functional group contributions in protein-ligand binding: a comprehensive study by crystallography and isothermal titration calorimetry.

PubMed

Baum, Bernhard; Muley, Laveena; Smolinski, Michael; Heine, Andreas; Hangauer, David; Klebe, Gerhard

2010-04-09

Additivity of functional group contributions to protein-ligand binding is a very popular concept in medicinal chemistry as the basis of rational design and optimized lead structures. Most of the currently applied scoring functions for docking build on such additivity models. Even though the limitation of this concept is well known, case studies examining in detail why additivity fails at the molecular level are still very scarce. The present study shows, by use of crystal structure analysis and isothermal titration calorimetry for a congeneric series of thrombin inhibitors, that extensive cooperative effects between hydrophobic contacts and hydrogen bond formation are intimately coupled via dynamic properties of the formed complexes. The formation of optimal lipophilic contacts with the surface of the thrombin S3 pocket and the full desolvation of this pocket can conflict with the formation of an optimal hydrogen bond between ligand and protein. The mutual contributions of the competing interactions depend on the size of the ligand hydrophobic substituent and influence the residual mobility of ligand portions at the binding site. Analysis of the individual crystal structures and factorizing the free energy into enthalpy and entropy demonstrates that binding affinity of the ligands results from a mixture of enthalpic contributions from hydrogen bonding and hydrophobic contacts, and entropic considerations involving an increasing loss of residual mobility of the bound ligands. This complex picture of mutually competing and partially compensating enthalpic and entropic effects determines the non-additivity of free energy contributions to ligand binding at the molecular level. (c) 2010 Elsevier Ltd. All rights reserved.

Studies for understanding effects of additions on the strength of cement concrete

NASA Astrophysics Data System (ADS)

Bucur, R. D.; Barbuta, M.; Konvalina, P.; Serbanoiu, A. A.; Bernas, J.

2017-09-01

The paper analyzes the effects of different types of additions introduced in concrete mix on the compressive strength. The current studies show that additions contribute to improve some characteristics of concrete and to reduce the cement dosage, so it can obtain concretes which are cheaper and friendlier with environment. In the experimental mixes were introduced: crushed natural aggregates, slag aggregates, silica fume, fly ash, chopped tire, polystyrene granule, glass fibers and metallic fibers. The experimental values of compressive strengths were compared for two concrete grades (C20/25 and C25/30). The study shown that near the well-known possibilities of improving mechanical strengths of cement concrete by increasing cement dosage and strength, by using crushed aggregates and by reducing the water/cement ratio, there are other methods in which less cement is used by replacing it with different wastes or by adding fiber.

78 FR 68461 - Guidance for Industry: Studies To Evaluate the Utility of Anti-Salmonella Chemical Food Additives...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-14

...] Guidance for Industry: Studies To Evaluate the Utility of Anti- Salmonella Chemical Food Additives in Feeds... Industry: Studies to Evaluate the Utility of Anti-Salmonella Chemical Food Additives in Feeds,'' and is... of Anti-Salmonella Chemical Food Additives in Feeds (GFI 80) is to help sponsors design efficacy...

Radiation combined injury models to study the effects of interventions and wound biomechanics.

PubMed

Zawaski, Janice A; Yates, Charles R; Miller, Duane D; Kaffes, Caterina C; Sabek, Omaima M; Afshar, Solmaz F; Young, Daniel A; Yang, Yunzhi; Gaber, M Waleed

2014-12-01

In the event of a nuclear detonation, a considerable number of projected casualties will suffer from combined radiation exposure and burn and/or wound injury. Countermeasure assessment in the setting of radiation exposure combined with dermal injury is hampered by a lack of animal models in which the effects of interventions have been characterized. To address this need, we used two separate models to characterize wound closure. The first was an open wound model in mice to study the effect of wound size in combination with whole-body 6 Gy irradiation on the rate of wound closure, animal weight and survival (morbidity). In this model the addition of interventions, wound closure, subcutaneous vehicle injection, topical antiseptic and topical antibiotics were studied to measure their effect on healing and survival. The second was a rat closed wound model to study the biomechanical properties of a healed wound at 10 days postirradiation (irradiated with 6 or 7.5 Gy). In addition, complete blood counts were performed and wound pathology by staining with hematoxylin and eosin, trichrome, CD68 and Ki67. In the mouse open wound model, we found that wound size and morbidity were positively correlated, while wound size and survival were negatively correlated. Regardless of the wound size, the addition of radiation exposure delayed the healing of the wound by approximately 5-6 days. The addition of interventions caused, at a minimum, a 30% increase in survival and improved mean survival by ∼9 days. In the rat closed wound model we found that radiation exposure significantly decreased all wound biomechanical measurements as well as white blood cell, platelet and red blood cell counts at 10 days post wounding. Also, pathological changes showed a loss of dermal structure, thickening of dermis, loss of collagen/epithelial hyperplasia and an increased density of macrophages. In conclusion, we have characterized the effect of a changing wound size in combination with radiation

A Dosing Study of Bevacizumab for Retinopathy of Prematurity: Late Recurrences and Additional Treatments.

PubMed

Wallace, David K; Dean, Trevano W; Hartnett, Mary Elizabeth; Kong, Lingkun; Smith, Lois E; Hubbard, G Baker; McGregor, Mary Lou; Jordan, Catherine O; Mantagos, Iason S; Bell, Edward F; Kraker, Raymond T

2018-06-07

Intravitreal bevacizumab is increasingly used to treat severe retinopathy of prematurity (ROP), but it enters the bloodstream, and there is concern that it may alter development of other organs. Previously we reported short-term outcomes of 61 infants enrolled in a dose de-escalation study, and we report the late recurrences and additional treatments. Masked, multicenter, dose de-escalation study. A total of 61 premature infants with type 1 ROP. If type 1 ROP was bilateral at enrollment, then the study eye was randomly selected. In the study eye, bevacizumab intravitreal injections were given at de-escalating doses of 0.25 mg, 0.125 mg, 0.063 mg, or 0.031 mg; if needed, fellow eyes received 1 dose level higher: 0.625 mg, 0.25 mg, 0.125 mg, or 0.063 mg, respectively. After 4 weeks, additional treatment was at the discretion of the investigator. Early and late ROP recurrences, additional treatments, and structural outcomes after 6 months. Of 61 study eyes, 25 (41%; 95% confidence interval [CI], 29%-54%) received additional treatment: 3 (5%; 95% CI, 1%-14%) for early failure (within 4 weeks), 11 (18%; 95% CI, 9%-30%) for late recurrence of ROP (after 4 weeks), and 11 (18%; 95% CI, 9%-30%) for persistent avascular retina. Re-treatment for early failure or late recurrence occurred in 2 of 11 eyes (18%; 95% CI, 2%-52%) treated with 0.25 mg, 4 of 16 eyes (25%; 95% CI, 7%-52%) treated with 0.125 mg, 8 of 24 eyes (33%; 95% CI, 16%-55%) treated with 0.063 mg, and 0 (0%; 95% CI, 0%-31%) of 10 eyes treated with 0.031 mg. By 6 months corrected age, 56 of 61 study eyes had regression of ROP with normal posterior poles, 1 study eye had developed a Stage 5 retinal detachment, and 4 infants had died of preexisting medical conditions. Retinal structural outcomes are very good after low-dose bevacizumab treatment for ROP, although many eyes received additional treatment. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

The impact of manual threshold selection in medical additive manufacturing.

PubMed

van Eijnatten, Maureen; Koivisto, Juha; Karhu, Kalle; Forouzanfar, Tymour; Wolff, Jan

2017-04-01

Medical additive manufacturing requires standard tessellation language (STL) models. Such models are commonly derived from computed tomography (CT) images using thresholding. Threshold selection can be performed manually or automatically. The aim of this study was to assess the impact of manual and default threshold selection on the reliability and accuracy of skull STL models using different CT technologies. One female and one male human cadaver head were imaged using multi-detector row CT, dual-energy CT, and two cone-beam CT scanners. Four medical engineers manually thresholded the bony structures on all CT images. The lowest and highest selected mean threshold values and the default threshold value were used to generate skull STL models. Geometric variations between all manually thresholded STL models were calculated. Furthermore, in order to calculate the accuracy of the manually and default thresholded STL models, all STL models were superimposed on an optical scan of the dry female and male skulls ("gold standard"). The intra- and inter-observer variability of the manual threshold selection was good (intra-class correlation coefficients >0.9). All engineers selected grey values closer to soft tissue to compensate for bone voids. Geometric variations between the manually thresholded STL models were 0.13 mm (multi-detector row CT), 0.59 mm (dual-energy CT), and 0.55 mm (cone-beam CT). All STL models demonstrated inaccuracies ranging from -0.8 to +1.1 mm (multi-detector row CT), -0.7 to +2.0 mm (dual-energy CT), and -2.3 to +4.8 mm (cone-beam CT). This study demonstrates that manual threshold selection results in better STL models than default thresholding. The use of dual-energy CT and cone-beam CT technology in its present form does not deliver reliable or accurate STL models for medical additive manufacturing. New approaches are required that are based on pattern recognition and machine learning algorithms.

Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model

ERIC Educational Resources Information Center

Keiner, Jason F.

2017-01-01

This qualitative case study explored the perceived experiences and outcomes of writing in a hybrid model of instruction in a large suburban high school. In particular, the impact of a hybrid model on the writing process and on future writing performance were examined. In addition, teacher expectation and teacher attitude and their impact upon…

Utilization of Titanium Particle Impact Location to Validate a 3D Multicomponent Model for Cold Spray Additive Manufacturing

NASA Astrophysics Data System (ADS)

Faizan-Ur-Rab, M.; Zahiri, S. H.; King, P. C.; Busch, C.; Masood, S. H.; Jahedi, M.; Nagarajah, R.; Gulizia, S.

2017-12-01

Cold spray is a solid-state rapid deposition technology in which metal powder is accelerated to supersonic speeds within a de Laval nozzle and then impacts onto the surface of a substrate. It is possible for cold spray to build thick structures, thus providing an opportunity for melt-less additive manufacturing. Image analysis of particle impact location and focused ion beam dissection of individual particles were utilized to validate a 3D multicomponent model of cold spray. Impact locations obtained using the 3D model were found to be in close agreement with the empirical data. Moreover, the 3D model revealed the particles' velocity and temperature just before impact—parameters which are paramount for developing a full understanding of the deposition process. Further, it was found that the temperature and velocity variations in large-size particles before impact were far less than for the small-size particles. Therefore, an optimal particle temperature and velocity were identified, which gave the highest deformation after impact. The trajectory of the particles from the injection point to the moment of deposition in relation to propellant gas is visualized. This detailed information is expected to assist with the optimization of the deposition process, contributing to improved mechanical properties for additively manufactured cold spray titanium parts.

How do humans inspect BPMN models: an exploratory study.

PubMed

Haisjackl, Cornelia; Soffer, Pnina; Lim, Shao Yi; Weber, Barbara

2018-01-01

Even though considerable progress regarding the technical perspective on modeling and supporting business processes has been achieved, it appears that the human perspective is still often left aside. In particular, we do not have an in-depth understanding of how process models are inspected by humans, what strategies are taken, what challenges arise, and what cognitive processes are involved. This paper contributes toward such an understanding and reports an exploratory study investigating how humans identify and classify quality issues in BPMN process models. Providing preliminary answers to initial research questions, we also indicate other research questions that can be investigated using this approach. Our qualitative analysis shows that humans adapt different strategies on how to identify quality issues. In addition, we observed several challenges appearing when humans inspect process models. Finally, we present different manners in which classification of quality issues was addressed.

Benchmarking DoD Use of Additive Manufacturing and Quantifying Costs

DTIC Science & Technology

2017-03-01

46 VI. Cost Benefit ...developing a cost model. The US Army Logistics Innovation Agency published a study called “Additive Manufacturing Cost - Benefit Analysis”. This...to over fifteen thousand dollars on GSA Advantage. Desktop printers do not require extensive support equipment. 47    VI. Cost Benefit

Fatigue Behavior and Modeling of Additively Manufactured Ti-6Al-4V Including Interlayer Time Interval Effects

NASA Astrophysics Data System (ADS)

Torries, Brian; Shamsaei, Nima

2017-12-01

The effects of different cooling rates, as achieved by varying the interlayer time interval, on the fatigue behavior of additively manufactured Ti-6Al-4V specimens were investigated and modeled via a microstructure-sensitive fatigue model. Comparisons are made between two sets of specimens fabricated via Laser Engineered Net Shaping (LENS™), with variance in interlayer time interval accomplished by depositing either one or two specimens per print operation. Fully reversed, strain-controlled fatigue tests were conducted, with fractography following specimen failure. A microstructure-sensitive fatigue model was calibrated to model the fatigue behavior of both sets of specimens and was found to be capable of correctly predicting the longer fatigue lives of the single-built specimens and the reduced scatter of the double-built specimens; all data points fell within the predicted upper and lower bounds of fatigue life. The time interval effects and the ability to be modeled are important to consider when producing test specimens that are smaller than the production part (i.e., property-performance relationships).

Estimation of a partially linear additive model for data from an outcome-dependent sampling design with a continuous outcome

PubMed Central

Tan, Ziwen; Qin, Guoyou; Zhou, Haibo

2016-01-01

Outcome-dependent sampling (ODS) designs have been well recognized as a cost-effective way to enhance study efficiency in both statistical literature and biomedical and epidemiologic studies. A partially linear additive model (PLAM) is widely applied in real problems because it allows for a flexible specification of the dependence of the response on some covariates in a linear fashion and other covariates in a nonlinear non-parametric fashion. Motivated by an epidemiological study investigating the effect of prenatal polychlorinated biphenyls exposure on children's intelligence quotient (IQ) at age 7 years, we propose a PLAM in this article to investigate a more flexible non-parametric inference on the relationships among the response and covariates under the ODS scheme. We propose the estimation method and establish the asymptotic properties of the proposed estimator. Simulation studies are conducted to show the improved efficiency of the proposed ODS estimator for PLAM compared with that from a traditional simple random sampling design with the same sample size. The data of the above-mentioned study is analyzed to illustrate the proposed method. PMID:27006375

Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance.

PubMed

Bernardo, R

1996-11-01

Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.

Using structured additive regression models to estimate risk factors of malaria: analysis of 2010 Malawi malaria indicator survey data.

PubMed

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.

Additional adjoint Monte Carlo studies of the shielding of concrete structures against initial gamma radiation. Final report

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

Beer, M.; Cohen, M.O.

1975-02-01

The adjoint Monte Carlo method previously developed by MAGI has been applied to the calculation of initial radiation dose due to air secondary gamma rays and fission product gamma rays at detector points within buildings for a wide variety of problems. These provide an in-depth survey of structure shielding effects as well as many new benchmark problems for matching by simplified models. Specifically, elevated ring source results were obtained in the following areas: doses at on-and off-centerline detectors in four concrete blockhouse structures; doses at detector positions along the centerline of a high-rise structure without walls; dose mapping at basementmore » detector positions in the high-rise structure; doses at detector points within a complex concrete structure containing exterior windows and walls and interior partitions; modeling of the complex structure by replacing interior partitions by additional material at exterior walls; effects of elevation angle changes; effects on the dose of changes in fission product ambient spectra; and modeling of mutual shielding due to external structures. In addition, point source results yielding dose extremes about the ring source average were obtained. (auth)« less

French and English Together: An "Additive" Experience

ERIC Educational Resources Information Center

Wiltshire, Jessica; Harbon, Lesley

2010-01-01

This paper examines the nature of the "additive" experience of a bilingual French-English curriculum at Killarney Heights Public School in New South Wales. Predictably, the well-supported "additive" nature of the languages program model elicited positive reactions regarding educational success. The paper also explores issues…

Introducing DeBRa: a detailed breast model for radiological studies

NASA Astrophysics Data System (ADS)

Ma, Andy K. W.; Gunn, Spencer; Darambara, Dimitra G.

2009-07-01

Currently, x-ray mammography is the method of choice in breast cancer screening programmes. As the mammography technology moves from 2D imaging modalities to 3D, conventional computational phantoms do not have sufficient detail to support the studies of these advanced imaging systems. Studies of these 3D imaging systems call for a realistic and sophisticated computational model of the breast. DeBRa (Detailed Breast model for Radiological studies) is the most advanced, detailed, 3D computational model of the breast developed recently for breast imaging studies. A DeBRa phantom can be constructed to model a compressed breast, as in film/screen, digital mammography and digital breast tomosynthesis studies, or a non-compressed breast as in positron emission mammography and breast CT studies. Both the cranial-caudal and mediolateral oblique views can be modelled. The anatomical details inside the phantom include the lactiferous duct system, the Cooper ligaments and the pectoral muscle. The fibroglandular tissues are also modelled realistically. In addition, abnormalities such as microcalcifications, irregular tumours and spiculated tumours are inserted into the phantom. Existing sophisticated breast models require specialized simulation codes. Unlike its predecessors, DeBRa has elemental compositions and densities incorporated into its voxels including those of the explicitly modelled anatomical structures and the noise-like fibroglandular tissues. The voxel dimensions are specified as needed by any study and the microcalcifications are embedded into the voxels so that the microcalcification sizes are not limited by the voxel dimensions. Therefore, DeBRa works with general-purpose Monte Carlo codes. Furthermore, general-purpose Monte Carlo codes allow different types of imaging modalities and detector characteristics to be simulated with ease. DeBRa is a versatile and multipurpose model specifically designed for both x-ray and γ-ray imaging studies.

Additive-Multiplicative Approximation of Genotype-Environment Interaction

PubMed Central

Gimelfarb, A.

1994-01-01

A model of genotype-environment interaction in quantitative traits is considered. The model represents an expansion of the traditional additive (first degree polynomial) approximation of genotypic and environmental effects to a second degree polynomial incorporating a multiplicative term besides the additive terms. An experimental evaluation of the model is suggested and applied to a trait in Drosophila melanogaster. The environmental variance of a genotype in the model is shown to be a function of the genotypic value: it is a convex parabola. The broad sense heritability in a population depends not only on the genotypic and environmental variances, but also on the position of the genotypic mean in the population relative to the minimum of the parabola. It is demonstrated, using the model, that GXE interaction rectional may cause a substantial non-linearity in offspring-parent regression and a reversed response to directional selection. It is also shown that directional selection may be accompanied by an increase in the heritability. PMID:7896113

Resource Tracking Model Updates and Trade Studies

NASA Technical Reports Server (NTRS)

Chambliss, Joe; Stambaugh, Imelda; Moore, Michael

2016-01-01

The Resource tracking model has been updated to capture system manager and project manager inputs. Both the Trick/GUNNS RTM simulator and the RTM mass balance spreadsheet have been revised to address inputs from system managers and to refine the way mass balance is illustrated. The revisions to the RTM included addition of a Plasma Pyrolysis Assembly (PPA) to recover hydrogen from Sabatier reactor methane which was vented in the prior version of the RTM. The effect of the PPA on the overall balance of resources in an exploration vehicle is illustrated in the increased recycle of vehicle oxygen. Additionally simulation of EVAs conducted from the exploration module was added. Since the focus of the exploration module is to provide a habitat during deep space operations the EVA simulation approach to EVA is based on ISS EVA protocol and processes. Case studies have been run to show the relative effect of performance changes on vehicle resources.

The Importance of Additive Reasoning in Children's Mathematical Achievement: A Longitudinal Study

ERIC Educational Resources Information Center

Ching, Boby Ho-Hong; Nunes, Terezinha

2017-01-01

This longitudinal study examines the relative importance of counting ability, additive reasoning, and working memory in children's mathematical achievement (calculation and story problem solving). In Hong Kong, 115 Chinese children aged 6 years old participated in 2 waves of assessments (T1 = first grade and T2 = second grade). Multiple regression…

Winston's "No Additives" campaign: "straight up"? "no bull"?

PubMed Central

Arnett, J J

1999-01-01

OBJECTIVE: The author used data from a larger study to examine adolescents' and adults' responses to Winston cigarettes' "No Additives" advertising campaign. METHODS: The author analyzed responses from 400 adolescents ages 12-17 and 203 adults ages 30-50 who were asked what they believed the meaning of the "No Additives" slogan to be. The author also analyzed adolescents' responses to questions about four specific Winston "No Additives" ads. RESULTS: Two-thirds of adolescents and 27% of adults believed that "No Additives" meant one or more of the following: that Winston cigarettes are healthier than other cigarettes, that they are less likely to harm health, or that they are less likely to be addictive. Adolescents perceived the models in three ads to be younger than 25 years old. Among adolescent respondents, smokers were more likely than nonsmokers to like the ads and to believe the ads made smoking more appealing. CONCLUSIONS: The "No Additives" slogan was perceived by a majority of adolescents and about a quarter of adults as implying one or more health claims. The results of this analysis suggest that the Federal Trade Commission's action in requiring a disclaimer on the "No Additives" ads is well founded but the disclaimer should be strengthened. PMID:10670619

Effects of a Tantalum Addition on the Morphological and Compositional Evolutions of a Model Ni-AL-Cr Superalloy

NASA Technical Reports Server (NTRS)

Booth-Morrison, Christopher; Seidman, David N.; Noebe, Ronald D.

2008-01-01

The effects of a 2.0 at.% addition of Ta to a model Ni-Al-Cr superalloy aged at 1073 K are assessed using scanning electron microscopy and atom-probe tomography. The addition of Ta results in appreciable strengthening, and the morphology is found to evolve from a bimodal distribution of spheroidal precipitates, to cuboidal precipitates aligned along the elastically soft <001>-type directions. Tantalum is observed to partition preferentially to the gamma -precipitate phase and decreases the mobility of Ni in the gamma- matrix sufficiently to cause an accumulation of Ni on the gamma-matrix side of the gamma -precipitate/gamma-matrix heterophase interface.

Postponed bifurcations of a ring-laser model with a swept parameter and additive colored noise

NASA Astrophysics Data System (ADS)

Mannella, R.; Moss, Frank; McClintock, P. V. E.

1987-03-01

The paper presents measurements of the time evolution of the statistical densities of both amplitude and field intensity obtained from a colored-noise-driven electronic circuit model of a ring laser, as the bifurcation parameter is swept through its critical values. The time-dependent second moments (intensities) were obtained from the densities. In addition, the individual stochastic trajectories were available from which the distribution of bifurcation times was constructed. For short-correlation-time (quasiwhite) noise the present results are in quantitative agreement with the recent calculations of Bogi, Colombo, Lugiato, and Mandel (1986). New results for long noise correlation times are obtained.

Replacing and Additive Horizontal Gene Transfer in Streptococcus

PubMed Central

Choi, Sang Chul; Rasmussen, Matthew D.; Hubisz, Melissa J.; Gronau, Ilan; Stanhope, Michael J.; Siepel, Adam

2012-01-01

The prominent role of Horizontal Gene Transfer (HGT) in the evolution of bacteria is now well documented, but few studies have differentiated between evolutionary events that predominantly cause genes in one lineage to be replaced by homologs from another lineage (“replacing HGT”) and events that result in the addition of substantial new genomic material (“additive HGT”). Here in, we make use of the distinct phylogenetic signatures of replacing and additive HGTs in a genome-wide study of the important human pathogen Streptococcus pyogenes (SPY) and its close relatives S. dysgalactiae subspecies equisimilis (SDE) and S. dysgalactiae subspecies dysgalactiae (SDD). Using recently developed statistical models and computational methods, we find evidence for abundant gene flow of both kinds within each of the SPY and SDE clades and of reduced levels of exchange between SPY and SDD. In addition, our analysis strongly supports a pronounced asymmetry in SPY–SDE gene flow, favoring the SPY-to-SDE direction. This finding is of particular interest in light of the recent increase in virulence of pathogenic SDE. We find much stronger evidence for SPY–SDE gene flow among replacing than among additive transfers, suggesting a primary influence from homologous recombination between co-occurring SPY and SDE cells in human hosts. Putative virulence genes are correlated with transfer events, but this correlation is found to be driven by additive, not replacing, HGTs. The genes affected by additive HGTs are enriched for functions having to do with transposition, recombination, and DNA integration, consistent with previous findings, whereas replacing HGTs seen to influence a more diverse set of genes. Additive transfers are also found to be associated with evidence of positive selection. These findings shed new light on the manner in which HGT has shaped pathogenic bacterial genomes. PMID:22617954

Numerical modelling and experimental study of liquid evaporation during gel formation

NASA Astrophysics Data System (ADS)

Pokusaev, B. G.; Khramtsov, D. P.

2017-11-01

Gels are promising materials in biotechnology and medicine as a medium for storing cells for bioprinting applications. Gel is a two-phase system consisting of solid medium and liquid phase. Understanding of a gel structure evolution and gel aging during liquid evaporation is a crucial step in developing new additive bioprinting technologies. A numerical and experimental study of liquid evaporation was performed. In experimental study an evaporation process of an agarose gel layer located on Petri dish was observed and mass difference was detected using electronic scales. Numerical model was based on a smoothed particle hydrodynamics method. Gel in a model was represented as a solid-liquid system and liquid evaporation was modelled due to capillary forces and heat transfer. Comparison of experimental data and numerical results demonstrated that model can adequately represent evaporation process in agarose gel.

Modelling Mass Movements for Planetary Studies

NASA Technical Reports Server (NTRS)

Bulmer, M. H.; Glaze, L.; Barnouin-Jha, O.; Murphy, W.; Neumann, G.

2002-01-01

Use of an empirical model in conjunction with data from the Chaos Jumbles rock avalanches constrain to first order their flow behavior, and provide a method to interpret rock/debris avalanche emplacement on Mars. Additional information is contained in the original extended abstract.

Additional EIPC Study Analysis: Interim Report on Medium Priority Topics

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

Hadley, Stanton W.; Gotham, Douglas J.

Between 2010 and 2012 the Eastern Interconnection Planning Collaborative (EIPC) conducted a major long-term resource and transmission study of the Eastern Interconnection (EI). With guidance from a stakeholder steering committee (SSC) that included representatives from the Eastern Interconnection States’ Planning Council (EISPC) among others, the project was conducted in two phases. The first was a 2015–2040 analysis that looked at a broad array of possible future scenarios, while the second focused on a more detailed examination of the grid in 2030. The studies provided a wealth of information on possible future generation, demand, and transmission alternatives. However, at the conclusionmore » there were still unresolved questions and issues. The US Department of Energy, which had sponsored the study, asked Oak Ridge National Laboratory researchers and others who worked on the project to conduct an additional study of the data to provide further insights for stakeholders and the industry. This report documents the second part of that follow-on study [an earlier report (Hadley 2013) covered the first part, and a subsequent report will address the last part].« less

Heat addition to a subsonic boundary layer: A preliminary analytical study

NASA Technical Reports Server (NTRS)

Macha, J. M.; Norton, D. J.

1971-01-01

A preliminary analytical study of the effects of heat addition to the subsonic boundary layer flow over a typical airfoil shape is presented. This phenomenon becomes of interest in the space shuttle mission since heat absorbed by the wing structure during re-entry will be rejected to the boundary layer during the subsequent low speed maneuvering and landing phase. A survey of existing literature and analytical solutions for both laminar and turbulent flow indicate that a heated surface generally destabilizes the boundary layer. Specifically, the boundary layer thickness is increased, the skin friction at the surface is decreased and the point of flow separation is moved forward. In addition, limited analytical results predict that the angle of attack at which a heated airfoil will stall is significantly less than the stall angle of an unheated wing. These effects could adversely affect the lift and drag, and thus the maneuvering capabilities of booster and orbiter shuttle vehicles.

Influence of additives on thermoresponsive polymers in aqueous media: a case study of poly(N-isopropylacrylamide).

PubMed

Umapathi, Reddicherla; Reddy, P Madhusudhana; Rani, Anjeeta; Venkatesu, Pannuru

2018-04-18

Thermoresponsive polymers (TRPs) in different solvent media have been studied over a long period and are important from both scientific and technical points of view. Despite numerous studies on the behavior of TRPs with various additives, the interactions of additives with TRPs are still poorly understood. Moreover, despite the vast available literature regarding the biomolecular interactions between various TRPs and naturally occurring additives, it is not possible to provide a unifying declaration about the behavior of different additives, in particular at the phase transition temperature of the polymer. However, potential reviews that describe the behavior of additives as stimuli upon the phase transition of TRPs are also absent. A lack of sufficient knowledge regarding the responses of TRPs to additives as stimuli has hindered the expansion of the wide spectrum of applications of these polymers. Therefore, it was proposed to review the responses of TRPs in the presence of various additives in aqueous media. In-depth knowledge acquired via a literature survey has drawn our attention towards filling this gap by analyzing the interactions of TRPs with different additives. In this perspective, we have systematically examined the stability, aggregation, and phase transition behaviours of various polymers in the presence of different additives. The perspective on the influence of additives as stimuli on the behavior of TRPs in an aqueous medium will provide new reliable information about intramolecular interactions between interior polymer segments as well as intermolecular interactions between TRPs and additive molecules, which will be helpful for industrialists in the preparation of new polymeric materials for drug-delivery systems.

Simultaneous masking additivity for short Gaussian-shaped tones: spectral effects.

PubMed

Laback, Bernhard; Necciari, Thibaud; Balazs, Peter; Savel, Sophie; Ystad, Sølvi

2013-08-01

Laback et al. [(2011). J. Acoust. Soc. Am. 129, 888-897] investigated the additivity of nonsimultaneous masking using short Gaussian-shaped tones as maskers and target. The present study involved Gaussian stimuli to measure the additivity of simultaneous masking for combinations of up to four spectrally separated maskers. According to most basilar membrane measurements, the maskers should be processed linearly at the characteristic frequency (CF) of the target. Assuming also compression of the target, all masker combinations should produce excess masking (exceeding linear additivity). The results for a pair of maskers flanking the target indeed showed excess masking. The amount of excess masking could be predicted by a model assuming summation of masker-evoked excitations in intensity units at the target CF and compression of the target, using compressive input/output functions derived from the nonsimultaneous masking study. However, the combinations of lower-frequency maskers showed much less excess masking than predicted by the model. This cannot easily be attributed to factors like off-frequency listening, combination tone perception, or between-masker suppression. It was better predicted, however, by assuming weighted intensity summation of masker excitations. The optimum weights for the lower-frequency maskers were smaller than one, consistent with partial masker compression as indicated by recent psychoacoustic data.

Using in vitro/in silico data for consumer safety assessment of feed flavoring additives--A feasibility study using piperine.

PubMed

Thiel, A; Etheve, S; Fabian, E; Leeman, W R; Plautz, J R

2015-10-01

Consumer health risk assessment for feed additives is based on the estimated human exposure to the additive that may occur in livestock edible tissues compared to its hazard. We present an approach using alternative methods for consumer health risk assessment. The aim was to use the fewest possible number of animals to estimate its hazard and human exposure without jeopardizing the safety upon use. As an example we selected the feed flavoring substance piperine and applied in silico modeling for residue estimation, results from literature surveys, and Read-Across to assess metabolism in different species. Results were compared to experimental in vitro metabolism data in rat and chicken, and to quantitative analysis of residues' levels from the in vivo situation in livestock. In silico residue modeling showed to be a worst case: the modeled residual levels were considerably higher than the measured residual levels. The in vitro evaluation of livestock versus rodent metabolism revealed no major differences in metabolism between the species. We successfully performed a consumer health risk assessment without performing additional animal experiments. As shown, the use and combination of different alternative methods supports animal welfare consideration and provides future perspective to reducing the number of animals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Modeling of digital mammograms using bicubic spline functions and additive noise

NASA Astrophysics Data System (ADS)

Graffigne, Christine; Maintournam, Aboubakar; Strauss, Anne

1998-09-01

The purpose of our work is the microcalcifications detection on digital mammograms. In order to do so, we model the grey levels of digital mammograms by the sum of a surface trend (bicubic spline function) and an additive noise or texture. We also introduce a robust estimation method in order to overcome the bias introduced by the microcalcifications. After the estimation we consider the subtraction image values as noise. If the noise is not correlated, we adjust its distribution probability by the Pearson's system of densities. It allows us to threshold accurately the images of subtraction and therefore to detect the microcalcifications. If the noise is correlated, a unilateral autoregressive process is used and its coefficients are again estimated by the least squares method. We then consider non overlapping windows on the residues image. In each window the texture residue is computed and compared with an a priori threshold. This provides correct localization of the microcalcifications clusters. However this technique is definitely more time consuming that then automatic threshold assuming uncorrelated noise and does not lead to significantly better results. As a conclusion, even if the assumption of uncorrelated noise is not correct, the automatic thresholding based on the Pearson's system performs quite well on most of our images.

Emerging technologies in arthroplasty: additive manufacturing.

PubMed

Banerjee, Samik; Kulesha, Gene; Kester, Mark; Mont, Michael A

2014-06-01

Additive manufacturing is an industrial technology whereby three-dimensional visual computer models are fabricated into physical components by selectively curing, depositing, or consolidating various materials in consecutive layers. Although initially developed for production of simulated models, the technology has undergone vast improvements and is currently increasingly being used for the production of end-use components in various aerospace, automotive, and biomedical specialties. The ability of this technology to be used for the manufacture of solid-mesh-foam monolithic and coated components of complex geometries previously considered unmanufacturable has attracted the attention of implant manufacturers, bioengineers, and orthopedic surgeons. Currently, there is a paucity of reports describing this fabrication method in the orthopedic literature. Therefore, we aimed to briefly describe this technology, some of the applications in other orthopedic subspecialties, its present use in hip and knee arthroplasty, and concerns with the present form of the technology. As there are few reports of clinical trials presently available, the true benefits of this technology can only be realized when studies evaluating the clinical and radiographic outcomes of cementless implants manufactured with additive manufacturing report durable fixation, less stress shielding, and better implant survivorship. Nevertheless, the authors believe that this technology holds great promise and may potentially change the conventional methods of casting, machining, and tooling for implant manufacturing in the future. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Gut Health of Pigs: Challenge Models and Response Criteria with a Critical Analysis of the Effectiveness of Selected Feed Additives — A Review

PubMed Central

Adewole, D. I.; Kim, I. H.; Nyachoti, C. M.

2016-01-01

The gut is the largest organ that helps with the immune function. Gut health, especially in young pigs has a significant benefit to health and performance. In an attempt to maintain and enhance intestinal health in pigs and improve productivity in the absence of in-feed antibiotics, researchers have evaluated a wide range of feed additives. Some of these additives such as zinc oxide, copper sulphate, egg yolk antibodies, mannan-oligosaccharides and spray dried porcine plasma and their effectiveness are discussed in this review. One approach to evaluate the effectiveness of these additives in vivo is to use an appropriate disease challenge model. Over the years, researchers have used a number of challenge models which include the use of specific strains of enterotoxigenic Escherichia coli, bacteria lipopolysaccharide challenge, oral challenge with Salmonella enteric serotype Typhimurium, sanitation challenge, and Lawsonia intercellularis challenge. These challenge models together with the criteria used to evaluate the responses of the animals to them are also discussed in this review. PMID:26954144

Effect of Ferrous Additives on Magnesia Stone Hydration

NASA Astrophysics Data System (ADS)

Zimich, V.

2017-11-01

The article deals with the modification of the magnesia binder with additives containing two- and three-valent iron cations which could be embedded in the chloromagnesium stone structure and also increase the strength from 60 MPa in a non-additive stone to 80MPa, water resistance from 0.58 for clear stone to 0.8 and reduce the hygroscopicity from 8% in the non-additive stone to 2% in the modified chloromagnesium stone. It is proposed to use the iron hydroxide sol as an additive in the quantities of up to 1% of the weight of the binder. The studies were carried out using the modern analysis methods: the differentialthermal and X-ray phase analysis. The structure was studied with an electron microscope with an X-ray microanalyzer. A two-factor plan-experiment was designed which allowed constructing mathematical models characterizing the influence of variable factors, such as the density of the zatcher and the amount of sol in the binder, on the basic properties of the magnesian stone. The result of the research was the magnesia stone with the claimed properties and formed from minerals characteristic for magnesian materials as well as additionally formed from amachenite and goethite. It has been established that a highly active iron hydroxide sol the ion sizes of which are commensurate with magnesium ions is actively incorporated into the structure of pentahydroxychloride and magnesium hydroxide changing the habit of crystals compacting the structure of the stone and changing its hygroscopicity.

One-range addition theorems for derivatives of Slater-type orbitals.

PubMed

Guseinov, Israfil

2004-06-01

Using addition theorems for STOs introduced by the author with the help of complete orthonormal sets of psi(alpha)-ETOs (Guseinov II (2003) J Mol Model 9:190-194), where alpha=1, 0, -1, -2, ..., a large number of one-range addition theorems for first and second derivatives of STOs are established. These addition theorems are especially useful for computation of multicenter-multielectron integrals over STOs that arise in the Hartree-Fock-Roothaan approximation and also in the Hylleraas function method, which play a significant role for the study of electronic structure and electron-nuclei interaction properties of atoms, molecules, and solids. The relationships obtained are valid for arbitrary quantum numbers, screening constants and location of STOs.

Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

PubMed Central

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

The prediction of food additives in the fruit juice based on electronic nose with chemometrics.

PubMed

Qiu, Shanshan; Wang, Jun

2017-09-01

Food additives are added to products to enhance their taste, and preserve flavor or appearance. While their use should be restricted to achieve a technological benefit, the contents of food additives should be also strictly controlled. In this study, E-nose was applied as an alternative to traditional monitoring technologies for determining two food additives, namely benzoic acid and chitosan. For quantitative monitoring, support vector machine (SVM), random forest (RF), extreme learning machine (ELM) and partial least squares regression (PLSR) were applied to establish regression models between E-nose signals and the amount of food additives in fruit juices. The monitoring models based on ELM and RF reached higher correlation coefficients (R 2 s) and lower root mean square errors (RMSEs) than models based on PLSR and SVM. This work indicates that E-nose combined with RF or ELM can be a cost-effective, easy-to-build and rapid detection system for food additive monitoring. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spectroscopic studies of model polar stratospheric cloud films

NASA Technical Reports Server (NTRS)

Tolbert, Margaret A.; Koehler, Birgit G.; Middlebrook, Ann M.

1993-01-01

Fourier transform infrared (FTIR) spectroscopy has been used to study nitric-acid/ice films representative of type I polar stratospheric clouds (PSCs). These studies reveal that in addition to amorphous nitric acid/ice mixtures, there are three stable stoichiometric hydrates of nitric acid: nitric-acid monohydrate (NAM), dihydrate (NAD), and trihydrate (NAT). We also observe two distinct crystalline forms of the trihydrate, which we denote alpha- and beta-NAT. These two forms appear to differ in their concentration of crystalline defects, but not in their chemical composition. In addition to probing the composition of type I PSCs, we have also used FTIR spectroscopy to study the interaction of HCl with model PSC films. In this work we find that for HCl pressures in the range 10 exp -5 to 10 exp -7 Torr, HCl is taken up by ice at 155 K to form a thin layer of HCl.6H2O. At 193 K, the uptake of HCl by ice was consistent with less than or equal to monolayer coverage. Uptake of HCl by alpha and beta-NAT at 175 K was also consistent with less than or equal to monolayer coverage.

A general circulation model study of atmospheric carbon monoxide

NASA Technical Reports Server (NTRS)

Pinto, J. P.; Rind, D.; Russell, G. L.; Lerner, J. A.; Hansen, J. E.; Yung, Y. L.; Hameed, S.

1983-01-01

The carbon monoxide cycle is studied by incorporating the known and hypothetical sources and sinks in a tracer model that uses the winds generated by a general circulation model. Photochemical production and loss terms, which depend on OH radical concentrations, are calculated in an interactive fashion. The computed global distribution and seasonal variations of CO are compared with observations to obtain constraints on the distribution and magnitude of the sources and sinks of CO, and on the tropospheric abundance of OH. The simplest model that accounts for available observations requires a low latitude plant source of about 1.3 x 10 to the 15th g/yr, in addition to sources from incomplete combustion of fossil fuels and oxidation of methane. The globally averaged OH concentration calculated in the model is 750,000/cu cm. Models that calculate globally averaged OH concentrations much lower than this nominal value are not consistent with the observed variability of CO. Such models are also inconsistent with measurements of CO isotopic abundances, which imply the existence of plant sources.

Additivity of Factor Effects in Reading Tasks Is Still a Challenge for Computational Models: Reply to Ziegler, Perry, and Zorzi (2009)

ERIC Educational Resources Information Center

Besner, Derek; O'Malley, Shannon

2009-01-01

J. C. Ziegler, C. Perry, and M. Zorzi (2009) have claimed that their connectionist dual process model (CDP+) can simulate the data reported by S. O'Malley and D. Besner. Most centrally, they have claimed that the model simulates additive effects of stimulus quality and word frequency on the time to read aloud when words and nonwords are randomly…

Characterization of metal additive manufacturing surfaces using synchrotron X-ray CT and micromechanical modeling

NASA Astrophysics Data System (ADS)

Kantzos, C. A.; Cunningham, R. W.; Tari, V.; Rollett, A. D.

2018-05-01

Characterizing complex surface topologies is necessary to understand stress concentrations created by rough surfaces, particularly those made via laser power-bed additive manufacturing (AM). Synchrotron-based X-ray microtomography (μ XCT) of AM surfaces was shown to provide high resolution detail of surface features and near-surface porosity. Using the CT reconstructions to instantiate a micromechanical model indicated that surface notches and near-surface porosity both act as stress concentrators, while adhered powder carried little to no load. Differences in powder size distribution had no direct effect on the relevant surface features, nor on stress concentrations. Conventional measurements of surface roughness, which are highly influenced by adhered powder, are therefore unlikely to contain the information relevant to damage accumulation and crack initiation.

Characterization of metal additive manufacturing surfaces using synchrotron X-ray CT and micromechanical modeling

NASA Astrophysics Data System (ADS)

Kantzos, C. A.; Cunningham, R. W.; Tari, V.; Rollett, A. D.

2017-12-01

Characterizing complex surface topologies is necessary to understand stress concentrations created by rough surfaces, particularly those made via laser power-bed additive manufacturing (AM). Synchrotron-based X-ray microtomography (μ XCT ) of AM surfaces was shown to provide high resolution detail of surface features and near-surface porosity. Using the CT reconstructions to instantiate a micromechanical model indicated that surface notches and near-surface porosity both act as stress concentrators, while adhered powder carried little to no load. Differences in powder size distribution had no direct effect on the relevant surface features, nor on stress concentrations. Conventional measurements of surface roughness, which are highly influenced by adhered powder, are therefore unlikely to contain the information relevant to damage accumulation and crack initiation.

GROUT HOPPER MODELING STUDY

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

Lee, S.

2011-08-30

The Saltstone facility has a grout hopper tank to provide agitator stirring of the Saltstone feed materials. The tank has about 300 gallon capacity to provide a larger working volume for the grout slurry to be held in case of a process upset, and it is equipped with a mechanical agitator, which is intended to keep the grout in motion and agitated so that it won't start to set up. The dry feeds and the salt solution are already mixed in the mixer prior to being transferred to the hopper tank. The hopper modeling study through this work will focusmore » on fluid stirring and agitation, instead of traditional mixing in the literature, in order to keep the tank contents in motion during their residence time so that they will not be upset or solidified prior to transferring the grout to the Saltstone disposal facility. The primary objective of the work is to evaluate the flow performance for mechanical agitators to prevent vortex pull-through for an adequate stirring of the feed materials and to estimate an agitator speed which provides acceptable flow performance with a 45{sup o} pitched four-blade agitator. In addition, the power consumption required for the agitator operation was estimated. The modeling calculations were performed by taking two steps of the Computational Fluid Dynamics (CFD) modeling approach. As a first step, a simple single-stage agitator model with 45{sup o} pitched propeller blades was developed for the initial scoping analysis of the flow pattern behaviors for a range of different operating conditions. Based on the initial phase-1 results, the phase-2 model with a two-stage agitator was developed for the final performance evaluations. A series of sensitivity calculations for different designs of agitators and operating conditions have been performed to investigate the impact of key parameters on the grout hydraulic performance in a 300-gallon hopper tank. For the analysis, viscous shear was modeled by using the Bingham plastic approximation

Additional disinfection with a modified salt solution in a root canal model.

PubMed

van der Waal, Suzette V; Oonk, Charlotte A M; Nieman, Selma H; Wesselink, Paul R; de Soet, Johannes J; Crielaard, Wim

2015-10-01

The aim of this study is to investigate the disinfecting properties of a modified salt solution (MSS) and calcium hydroxide (Ca(OH)2) in a non-direct-contact ex-vivo model. Seventy-four single-canal roots infected with Enterococcus faecalis were treated with 1% sodium hypochlorite (NaOCl) irrigation or with NaOCl irrigation with subsequent dressing with MSS or Ca(OH)2. After removal of the dressings, the roots were filled with bacterial growth medium and incubated for seven days to enable the surviving bacteria to repopulate the root canal lumen. Growth was determined by sampling the root canals with paper points before treatment (S1), after treatment (S2) and incubation after treatment (S3). The colony forming units were counted at S1 and S2. At S3, growth was determined as no/yes regrowth. The Kruskal-Wallis, McNemar and χ(2) test were used for statistical analyses. At S2, in the NaOCl group, growth was found in 5 of 19 root canals. After the removal of MSS or Ca(OH)2 bacteria were retrieved from one root canal in both groups. At S3, repopulation of the root canals had occurred in 14 of 19 roots after sole NaOCl irrigation, 6 of 20 roots after MSS-dressing and in 14 of 20 roots after Ca(OH)2-dressing. MSS was more effective in preventing regrowth than Ca(OH)2 (P=0.009). The modified salt solution prevented regrowth in roots which indicates that it can eliminate persistent bacteria. Dressing the root canals with Ca(OH)2 did not provide additional disinfection after NaOCl irrigation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mechanistic Study of Electrolyte Additives to Stabilize High-Voltage Cathode-Electrolyte Interface in Lithium-Ion Batteries.

PubMed

Gao, Han; Maglia, Filippo; Lamp, Peter; Amine, Khalil; Chen, Zonghai

2017-12-27

Current developments of electrolyte additives to stabilize electrode-electrolyte interface in lithium-ion batteries highly rely on a trial-and-error search, which involves repetitive testing and intensive amount of resources. The lack of understandings on the fundamental protection mechanisms of the additives significantly increases the difficulty for the transformational development of new additives. In this study, we investigated two types of individual protection routes to build a robust cathode-electrolyte interphase at high potentials: (i) a direct reduction in the catalytic decomposition of the electrolyte solvent; and (ii) formation of a "corrosion inhibitor film" that prevents severely attack and passivation from protons that generated from the solvent oxidation, even the decomposition of solvent cannot be mitigated. Effect of two exemplary electrolyte additives, lithium difluoro(oxalato)borate (LiDFOB) and 3-hexylthiophene (3HT), on LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC 622) cathode were investigated to validate our hypothesis. It is demonstrated that understandings of both electrolyte additives and solvent are essential and careful balance between the cathode protection mechanism of additives and their side effects is critical to obtain optimum results. More importantly, this study opens up new directions of rational design of functional electrolyte additives for the next-generation high-energy-density lithium-ion chemistries.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to

Analysis of habitat characteristics of small pelagic fish based on generalized additive models in Kepulauan Seribu Waters

NASA Astrophysics Data System (ADS)

Rivai, A. A.; Siregar, V. P.; Agus, S. B.; Yasuma, H.

2018-03-01

One of the required information for sustainable fisheries management is about the habitat characteristics of a fish species. This information can be used to map the distribution of fish and map the potential fishing ground. This study aimed to analyze the habitat characteristics of small pelagic fishes (anchovy, squid, sardine and scads) which were mainly caught by lift net in Kepulauan Seribu waters. Research on habitat characteristics had been widely done, but the use of total suspended solid (TSS) parameters in this analysis is still lacking. TSS parameter which was extracted from Landsat 8 along with five other oceanographic parameters, CPUE data and location of fishing ground data from lift net fisheries in Kepulauan Seribu were included in this analysis. This analysis used Generalized Additive Models (GAMs) to evaluate the relationship between CPUE and oceanographic parameters. The results of the analysis showed that each fish species had different habitat characteristics. TSS and sea surface height had a great influence on the value of CPUE from each species. All the oceanographic parameters affected the CPUE of each species. This study demonstrated the effective use of GAMs to identify the essential habitat of a fish species.

New addition curing polyimides

NASA Technical Reports Server (NTRS)

Frimer, Aryeh A.; Cavano, Paul

1991-01-01

In an attempt to improve the thermal-oxidative stability (TOS) of PMR-type polymers, the use of 1,4-phenylenebis (phenylmaleic anhydride) PPMA, was evaluated. Two series of nadic end-capped addition curing polyimides were prepared by imidizing PPMA with either 4,4'-methylene dianiline or p-phenylenediamine. The first resulted in improved solubility and increased resin flow while the latter yielded a compression molded neat resin sample with a T(sub g) of 408 C, close to 70 C higher than PME-15. The performance of these materials in long term weight loss studies was below that of PMR-15, independent of post-cure conditions. These results can be rationalized in terms of the thermal lability of the pendant phenyl groups and the incomplete imidization of the sterically congested PPMA. The preparation of model compounds as well as future research directions are discussed.

A novel small animal model to study the replication of simian foamy virus in vivo.

PubMed

Blochmann, Rico; Curths, Christoph; Coulibaly, Cheick; Cichutek, Klaus; Kurth, Reinhard; Norley, Stephen; Bannert, Norbert; Fiebig, Uwe

2014-01-05

Preclinical evaluation in a small animal model would help the development of gene therapies and vaccines based on foamy virus vectors. The establishment of persistent, non-pathogenic infection with the prototype foamy virus in mice and rabbits has been described previously. To extend this spectrum of available animal models, hamsters were inoculated with infectious cell supernatant or bioballistically with a foamy virus plasmid. In addition, a novel foamy virus from a rhesus macaque was isolated and characterised genetically. Hamsters and mice were infected with this new SFVmac isolate to evaluate whether hamsters are also susceptible to infection. Both hamsters and mice developed humoral responses to either virus subtype. Virus integration and replication in different animal tissues were analysed by PCR and co-cultivation. The results strongly indicate establishment of a persistent infection in hamsters. These studies provide a further small animal model for studying FV-based vectors in addition to the established models. © 2013 Elsevier Inc. All rights reserved.

Additive direct-write microfabrication for MEMS: A review

NASA Astrophysics Data System (ADS)

Teh, Kwok Siong

2017-12-01

Direct-write additive manufacturing refers to a rich and growing repertoire of well-established fabrication techniques that builds solid objects directly from computer- generated solid models without elaborate intermediate fabrication steps. At the macroscale, direct-write techniques such as stereolithography, selective laser sintering, fused deposition modeling ink-jet printing, and laminated object manufacturing have significantly reduced concept-to-product lead time, enabled complex geometries, and importantly, has led to the renaissance in fabrication known as the maker movement. The technological premises of all direct-write additive manufacturing are identical—converting computer generated three-dimensional models into layers of two-dimensional planes or slices, which are then reconstructed sequentially into threedimensional solid objects in a layer-by-layer format. The key differences between the various additive manufacturing techniques are the means of creating the finished layers and the ancillary processes that accompany them. While still at its infancy, direct-write additive manufacturing techniques at the microscale have the potential to significantly lower the barrier-of-entry—in terms of cost, time and training—for the prototyping and fabrication of MEMS parts that have larger dimensions, high aspect ratios, and complex shapes. In recent years, significant advancements in materials chemistry, laser technology, heat and fluid modeling, and control systems have enabled additive manufacturing to achieve higher resolutions at the micrometer and nanometer length scales to be a viable technology for MEMS fabrication. Compared to traditional MEMS processes that rely heavily on expensive equipment and time-consuming steps, direct-write additive manufacturing techniques allow for rapid design-to-prototype realization by limiting or circumventing the need for cleanrooms, photolithography and extensive training. With current direct-write additive

Thermal Vegetation Canopy Model Studies.

DTIC Science & Technology

1981-08-01

optical and thermal canopy radiation models, and the interpretation of these measurements. Previous technical re- ports in this series have described...The initial guess is taken to be air temperature; thus, the solution approach may be interpreted as determining the modification to the air...provided assistance for interpreting the micrometeorological data. In addition, Dr. L. W. Gay of the School of Renewable Natural Resources, Arizona

Individualized Additional Instruction for Calculus

ERIC Educational Resources Information Center

Takata, Ken

2010-01-01

College students enrolling in the calculus sequence have a wide variance in their preparation and abilities, yet they are usually taught from the same lecture. We describe another pedagogical model of Individualized Additional Instruction (IAI) that assesses each student frequently and prescribes further instruction and homework based on the…

Using a logic model to evaluate the Kids Together early education inclusion program for children with disabilities and additional needs.

PubMed

Clapham, Kathleen; Manning, Claire; Williams, Kathryn; O'Brien, Ginger; Sutherland, Margaret

2017-04-01

Despite clear evidence that learning and social opportunities for children with disabilities and special needs are more effective in inclusive not segregated settings, there are few known effective inclusion programs available to children with disabilities, their families or teachers in the early years within Australia. The Kids Together program was developed to support children with disabilities/additional needs aged 0-8 years attending mainstream early learning environments. Using a key worker transdisciplinary team model, the program aligns with the individualised package approach of the National Disability Insurance Scheme (NDIS). This paper reports on the use of a logic model to underpin the process, outcomes and impact evaluation of the Kids Together program. The research team worked across 15 Early Childhood Education and Care (ECEC) centres and in home and community settings. A realist evaluation using mixed methods was undertaken to understand what works, for whom and in what contexts. The development of a logic model provided a structured way to explore how the program was implemented and achieved short, medium and long term outcomes within a complex community setting. Kids Together was shown to be a highly effective and innovative model for supporting the inclusion of children with disabilities/additional needs in a range of environments central for early childhood learning and development. The use of a logic model provided a visual representation of the Kids Together model and its component parts and enabled a theory of change to be inferred, showing how a coordinated and collaborative approached can work across multiple environments. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of Exogenous Phytase Addition on Soil Phosphatase Activities: a Fluorescence Spectroscopy Study.

PubMed

Yang, Xiao-zhu; Chen, Zhen-hua; Zhang, Yu-lan; Chen, Li-jun

2015-05-01

The utilization of organic phosphorus (P) has directly or indirectly improved after exogenous phytase was added to soil. However, the mechanism by which exogenous phytase affected the soil phosphatases (phosphomonoesterase and phosphodiesterase) activities was not clear. The present work was aimed to study red soil, brown soil and cinnamon soil phosphomonoesterase (acid and alkaline) (AcP and AlP) and phosphodiesterase (PD) activities responding to the addition of exogenous phytase (1 g phytase/50 g air dry soil sample) based on the measurements performed via a fluorescence detection method combined with 96 microplates using a TECAN Infinite 200 Multi-Mode Microplate Reader. The results indicated that the acid phosphomonoesterase activity was significantly enhanced in red soil (p≤0. 01), while it was significantly reduced in cinnamon soil; alkaline phosphomonoesterase activity was significantly enhanced in cinnamon soil (p≤ 0. 01), while it was significantly reduced in red soil; phosphodiesterase activity was increased in three soils but it was significantly increased in brown soil (p≤0. 01) after the addition of exogenous phytase. The activities still remained strong after eight days in different soils, which indicated that exogenous phytase addition could be enhance soil phosphatases activities effectively. This effect was not only related to soil properties, such as pH and phosphorus forms, but might also be related to the excreted enzyme amount of the stimulating microorganism. Using fluorescence spectroscopy to study exogenous phytase addition influence on soil phosphatase activities was the first time at home and abroad. Compared with the conventional spectrophotometric method, the fluorescence microplate method is an accurate, fast and simple to use method to determine the relationships among the soil phosphatases activities.

Fidelity study of superconductivity in extended Hubbard models

NASA Astrophysics Data System (ADS)

Plonka, N.; Jia, C. J.; Wang, Y.; Moritz, B.; Devereaux, T. P.

2015-07-01

The Hubbard model with local on-site repulsion is generally thought to possess a superconducting ground state for appropriate parameters, but the effects of more realistic long-range Coulomb interactions have not been studied extensively. We study the influence of these interactions on superconductivity by including nearest- and next-nearest-neighbor extended Hubbard interactions in addition to the usual on-site terms. Utilizing numerical exact diagonalization, we analyze the signatures of superconductivity in the ground states through the fidelity metric of quantum information theory. We find that nearest and next-nearest neighbor interactions have thresholds above which they destabilize superconductivity regardless of whether they are attractive or repulsive, seemingly due to competing charge fluctuations.

Additives

NASA Technical Reports Server (NTRS)

Smalheer, C. V.

1973-01-01

The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.

Using Generalized Additive Models to Analyze Single-Case Designs

ERIC Educational Resources Information Center

Shadish, William; Sullivan, Kristynn

2013-01-01

Many analyses for single-case designs (SCDs)--including nearly all the effect size indicators-- currently assume no trend in the data. Regression and multilevel models allow for trend, but usually test only linear trend and have no principled way of knowing if higher order trends should be represented in the model. This paper shows how Generalized…

Biocontrol of Listeria monocytogenes in a meat model using a combination of a bacteriocinogenic strain with curing additives.

PubMed

Orihuel, Alejandra; Bonacina, Julieta; Vildoza, María José; Bru, Elena; Vignolo, Graciela; Saavedra, Lucila; Fadda, Silvina

2018-05-01

The aim of this work was to evaluate the effect of meat curing agents on the bioprotective activity of the bacteriocinogenic strain, Enterococcus (E.) mundtii CRL35 against Listeria (L.) monocytogenes during meat fermentation. The ability of E. mundtii CRL35 to grow, acidify and produce bacteriocin in situ was assayed in a meat model system in the presence of curing additives (CA). E. mundtii CRL35 showed optimal growth and acidification rates in the presence of CA. More importantly, the highest bacteriocin titer was achieved in the presence of these food agents. In addition, the CA produced a statistical significant enhancement of the enterocin CRL35 activity. This positive effect was demonstrated in vitro in a meat based culture medium, by time-kill kinetics and finally by using a beaker sausage model with a challenge experiment with the pathogenic L. monocytogenes FBUNT strain. E. mundtii CRL35 was found to be a promising strain of use as a safety adjunct culture in meat industry and a novel functional supplement for sausage fermentation, ensuring hygiene and quality of the final product. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mars-GRAM 2010: Additions and Resulting Improvements

NASA Technical Reports Server (NTRS)

Justh, Hilary L.; Burns, K. Lee

2013-01-01

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM has been utilized during previous aerobraking operations in the atmosphere of Mars. Mars-GRAM has also been used in the prediction and validation of Mars Pathfinder hypersonic aerodynamics, the aerothermodynamic and entry dynamics studies for Mars Polar Lander, the landing site selection process for the Mars Science Laboratory (MSL), the Mars Aerocapture System Study (MASS) as well as the Aerocapture Technology Assessment Group (TAG). Most recently, Mars-GRAM 2010 was used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. The most recent release of Mars-GRAM 2010 contains several changes including an update to Fortran 90/95 and the addition of adjustment factors. Following the completion of a comparison analysis between Mars-GRAM, Thermal Emission Spectrometer (TES), as well as Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) aerobraking density data, adjustment factors were added to Mars-GRAM 2010 that alter the input data from National Aeronautics and Space Administration (NASA) Ames Mars General Circulation Model (MGCM) and the University of Michigan Mars Thermospheric General Circulation Model (MTGCM) for the mapping year 0 user-controlled dust case. The addition of adjustment factors resolved the issue of previous versions of Mars-GRAM being less than realistic when used for sensitivity studies for mapping year 0 and large optical depth values, such as tau equal to 3. Mars-GRAM was evaluated at locations and times of TES limb observations and adjustment factors were determined. For altitudes above 80 km and below 135 km, Mars-GRAM (MTGCM) densities were compared to aerobraking densities measured by Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) to determine the adjustment

Mechanistic Study of Electrolyte Additives to Stabilize High-Voltage Cathode–Electrolyte Interface in Lithium-Ion Batteries

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

Gao, Han; Maglia, Filippo; Lamp, Peter

Current developments of electrolyte additives to stabilize electrode-electrolyte interface in Li-ion batteries highly rely on a trial-and-error search, which involves repetitive testing and intensive amount of resources. The lack of understandings on the fundamental protection mechanisms of the additives significantly increases the difficulty for the transformational development of new additives. In this study, we investigated two types of individual protection routes to build a robust cathode-electrolyte interphase at high potentials: (i) a direct reduction in the catalytic decomposition of the electrolyte solvent; and (ii) formation of a “corrosion inhibitor film” that prevents severely attack and passivation from protons that generatedmore » from the solvent oxidation, even the decomposition of solvent cannot not mitigated. Effect of three exemplary electrolyte additives: (i) lithium difluoro(oxalato)borate (LiDFOB); (ii) 3-hexylthiophene (3HT); and (iii) tris(hexafluoro-iso-propyl)phosphate (HFiP), on LiNi0.6Mn0.2Co0.2O2 (NMC 622) cathode were investigated to validate our hypothesis. It is demonstrated that understandings of both electrolyte additives and solvent are essential and careful balance between the cathode protection mechanism of additives and their side effects is critical to obtain optimum results. More importantly, this study opens up new directions of rational design of functional electrolyte additives for the next generation high-energy density lithium-ion chemistries.« less

Data-driven multi-scale multi-physics models to derive process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Lian, Yanping; Yu, Cheng; Liu, Zeliang; Yan, Jinhui; Wolff, Sarah; Wu, Hao; Ndip-Agbor, Ebot; Mozaffar, Mojtaba; Ehmann, Kornel; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-05-01

Additive manufacturing (AM) possesses appealing potential for manipulating material compositions, structures and properties in end-use products with arbitrary shapes without the need for specialized tooling. Since the physical process is difficult to experimentally measure, numerical modeling is a powerful tool to understand the underlying physical mechanisms. This paper presents our latest work in this regard based on comprehensive material modeling of process-structure-property relationships for AM materials. The numerous influencing factors that emerge from the AM process motivate the need for novel rapid design and optimization approaches. For this, we propose data-mining as an effective solution. Such methods—used in the process-structure, structure-properties and the design phase that connects them—would allow for a design loop for AM processing and materials. We hope this article will provide a road map to enable AM fundamental understanding for the monitoring and advanced diagnostics of AM processing.

Generalized additive models and Lucilia sericata growth: assessing confidence intervals and error rates in forensic entomology.

PubMed

Tarone, Aaron M; Foran, David R

2008-07-01

Forensic entomologists use blow fly development to estimate a postmortem interval. Although accurate, fly age estimates can be imprecise for older developmental stages and no standard means of assigning confidence intervals exists. Presented here is a method for modeling growth of the forensically important blow fly Lucilia sericata, using generalized additive models (GAMs). Eighteen GAMs were created to predict the extent of juvenile fly development, encompassing developmental stage, length, weight, strain, and temperature data, collected from 2559 individuals. All measures were informative, explaining up to 92.6% of the deviance in the data, though strain and temperature exerted negligible influences. Predictions made with an independent data set allowed for a subsequent examination of error. Estimates using length and developmental stage were within 5% of true development percent during the feeding portion of the larval life cycle, while predictions for postfeeding third instars were less precise, but within expected error.

Data-driven multi-scale multi-physics models to derive process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Lian, Yanping; Yu, Cheng; Liu, Zeliang; Yan, Jinhui; Wolff, Sarah; Wu, Hao; Ndip-Agbor, Ebot; Mozaffar, Mojtaba; Ehmann, Kornel; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-01-01

Additive manufacturing (AM) possesses appealing potential for manipulating material compositions, structures and properties in end-use products with arbitrary shapes without the need for specialized tooling. Since the physical process is difficult to experimentally measure, numerical modeling is a powerful tool to understand the underlying physical mechanisms. This paper presents our latest work in this regard based on comprehensive material modeling of process-structure-property relationships for AM materials. The numerous influencing factors that emerge from the AM process motivate the need for novel rapid design and optimization approaches. For this, we propose data-mining as an effective solution. Such methods—used in the process-structure, structure-properties and the design phase that connects them—would allow for a design loop for AM processing and materials. We hope this article will provide a road map to enable AM fundamental understanding for the monitoring and advanced diagnostics of AM processing.

Defining an additivity framework for mixture research in inducible whole-cell biosensors

NASA Astrophysics Data System (ADS)

Martin-Betancor, K.; Ritz, C.; Fernández-Piñas, F.; Leganés, F.; Rodea-Palomares, I.

2015-11-01

A novel additivity framework for mixture effect modelling in the context of whole cell inducible biosensors has been mathematically developed and implemented in R. The proposed method is a multivariate extension of the effective dose (EDp) concept. Specifically, the extension accounts for differential maximal effects among analytes and response inhibition beyond the maximum permissive concentrations. This allows a multivariate extension of Loewe additivity, enabling direct application in a biphasic dose-response framework. The proposed additivity definition was validated, and its applicability illustrated by studying the response of the cyanobacterial biosensor Synechococcus elongatus PCC 7942 pBG2120 to binary mixtures of Zn, Cu, Cd, Ag, Co and Hg. The novel method allowed by the first time to model complete dose-response profiles of an inducible whole cell biosensor to mixtures. In addition, the approach also allowed identification and quantification of departures from additivity (interactions) among analytes. The biosensor was found to respond in a near additive way to heavy metal mixtures except when Hg, Co and Ag were present, in which case strong interactions occurred. The method is a useful contribution for the whole cell biosensors discipline and related areas allowing to perform appropriate assessment of mixture effects in non-monotonic dose-response frameworks

A Longitudinal Field Study Comparing a Multiplicative and an Additive Model of Motivation and Ability. Technical Report No. 11.

ERIC Educational Resources Information Center

Barrett, Gerald V.; And Others

The relative contribution of motivation to ability measures in predicting performance criteria of sales personnel from successive fiscal periods was investigated. In this context, the merits of a multiplicative and additive combination of motivation and ability measures were examined. The relationship between satisfaction and motivation and…

Food additives.

PubMed

Berglund, F

1978-01-01

The use of additives to food fulfils many purposes, as shown by the index issued by the Codex Committee on Food Additives: Acids, bases and salts; Preservatives, Antioxidants and antioxidant synergists; Anticaking agents; Colours; Emulfifiers; Thickening agents; Flour-treatment agents; Extraction solvents; Carrier solvents; Flavours (synthetic); Flavour enhancers; Non-nutritive sweeteners; Processing aids; Enzyme preparations. Many additives occur naturally in foods, but this does not exclude toxicity at higher levels. Some food additives are nutrients, or even essential nutritents, e.g. NaCl. Examples are known of food additives causing toxicity in man even when used according to regulations, e.g. cobalt in beer. In other instances, poisoning has been due to carry-over, e.g. by nitrate in cheese whey - when used for artificial feed for infants. Poisonings also occur as the result of the permitted substance being added at too high levels, by accident or carelessness, e.g. nitrite in fish. Finally, there are examples of hypersensitivity to food additives, e.g. to tartrazine and other food colours. The toxicological evaluation, based on animal feeding studies, may be complicated by impurities, e.g. orthotoluene-sulfonamide in saccharin; by transformation or disappearance of the additive in food processing in storage, e.g. bisulfite in raisins; by reaction products with food constituents, e.g. formation of ethylurethane from diethyl pyrocarbonate; by metabolic transformation products, e.g. formation in the gut of cyclohexylamine from cyclamate. Metabolic end products may differ in experimental animals and in man: guanylic acid and inosinic acid are metabolized to allantoin in the rat but to uric acid in man. The magnitude of the safety margin in man of the Acceptable Daily Intake (ADI) is not identical to the "safety factor" used when calculating the ADI. The symptoms of Chinese Restaurant Syndrome, although not hazardous, furthermore illustrate that the whole ADI

Antiandrogenic activity of phthalate mixtures: Validity of concentration addition

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

Christen, Verena; Crettaz, Pierre; Oberli-Schrämmli, Aurelia

2012-03-01

Phthalates and bisphenol A have very widespread use leading to significant exposure of humans. They are suspected to interfere with the endocrine system, including the androgen, estrogen and the thyroid hormone system. Here we analyzed the antiandrogenic activity of six binary, and one ternary mixture of phthalates exhibiting complete antiandrogenic dose–response curves, and binary mixtures of phthalates and bisphenol A at equi-effective concentrations of EC{sub 10}, EC{sub 25} and EC{sub 50} in MDA-kb2 cells. Mixture activity followed the concentration addition (CA) model with a tendency to synergism at high and antagonism at low concentrations. Isoboles and the toxic unit approachmore » (TUA) confirmed the additive to synergistic activity of the binary mixtures BBP + DBP, DBP + DEP and DEP + BPA at high concentrations. Both methods indicate a tendency to antagonism for the EC{sub 10} mixtures BBP + DBP, BBP + DEP and DBP + DEP, and the EC{sub 25} mixture of DBP + BPA. A ternary mixture revealed synergism at the EC{sub 50}, and weak antagonistic activity at the EC{sub 25} level by the TUA. A mixture of five phthalates representing a human urine composition and reflecting exposure to corresponding parent compounds showed no antiandrogenic activity. Our study demonstrates that CA is an appropriate concept to account for mixture effects of antiandrogenic phthalates and bisphenol A. The interaction indicates a departure from additivity to antagonism at low concentrations, probably due to interaction with the androgen receptor and/or cofactors. This study emphasizes that a risk assessment of phthalates should account for mixture effects by applying the CA concept. -- Highlights: ► Antiandrogenic activity of mixtures of 2 and 3 phthalates are assessed in MDA-kb2 cells. ► Mixture activities followed the concentration addition model. ► A tendency to synergism at high and antagonism at low levels occurred.« less

The relation between air pollution and respiratory deaths in Tehran, Iran- using generalized additive models.

PubMed

Dehghan, Azizallah; Khanjani, Narges; Bahrampour, Abbas; Goudarzi, Gholamreza; Yunesian, Masoud

2018-03-20

Some epidemiological evidence has shown a relation between ambient air pollution and adverse health outcomes. The aim of this study was to investigate the effect of air pollution on mortality from respiratory diseases in Tehran, Iran. In this ecological study, air pollution data was inquired from the Tehran Province Environmental Protection Agency and the Tehran Air Quality Control Company. Meteorological data was collected from the Tehran Meteorology Organization and mortality data from the Tehran Cemetery Mortality Registration. Generalized Additive Models (GAM) was used for data analysis with different lags, up to 15 days. A 10-unit increase in all pollutants except CO (1-unit) was used to compute the Relative Risk of deaths. During 2005 until 2014, 37,967 respiratory deaths occurred in Tehran in which 21,913 (57.7%) were male. The strongest relationship between NO 2 and PM 10 and respiratory death was seen on the same day (lag 0), and was respectively (RR = 1.04, 95% CI: 1.02-1.07) and (RR = 1.03, 95% CI: 1.02-1.04). O 3 and PM 2.5 had the strongest relationship with respiratory deaths on lag 2 and 1 respectively, and the RR was equal to 1.03, 95% CI: 1.01-1.05 and 1.06, 95% CI: 1.02-1.10 respectively. NO 2 , O 3 , PM 10 and PM 2.5 also showed significant relations with respiratory deaths in the older age groups. The findings of this study showed that O 3 , NO 2 , PM 10 and PM 2.5 air pollutants were related to respiratory deaths in Tehran. Reducing ambient air pollution can save lives in Tehran.

Improving the accessibility and re-use of environmental models through provision of model metadata - a scoping study

NASA Astrophysics Data System (ADS)

Riddick, Andrew; Hughes, Andrew; Harpham, Quillon; Royse, Katherine; Singh, Anubha

2014-05-01

environment and the model code used, to assist the selection of models for linked compositions. Existing best practice, including the use of current metadata standards (e.g. ISO 19110, ISO 19115 and ISO 19119) and the metadata components of WaterML were also evaluated. In addition to commonly used metadata attributes (e.g. spatial reference information) there was significant interest in recording a variety of additional metadata attributes. These included more detailed information about temporal data, and also providing estimates of data accuracy and uncertainty within metadata. This poster describes the key results of this study, including a number of gaps in the provision of metadata for modelling, and outlines how these might be addressed. Overall the scoping study has highlighted significant interest in addressing this issue within the environmental modelling community. There is therefore an impetus for on-going research, and we are seeking to take this forward through collaboration with other interested organisations. Progress towards an internationally recognised model metadata standard is suggested.

Small angle neutron scattering study of sodium dodecyl sulfate micellar growth driven by addition of a hydrotropic salt.

PubMed

Hassan, P A; Fritz, Gerhard; Kaler, Eric W

2003-01-01

The structures of aggregates formed in aqueous solutions of an anionic surfactant, sodium dodecyl sulfate (SDS), with the addition of a cationic hydrotropic salt, p-toluidine hydrochloride (PTHC), have been investigated by small angle neutron scattering (SANS). The SANS spectra exhibit a pronounced peak at low salt concentration, indicating the presence of repulsive intermicellar interactions. Model-independent real space information about the structure is obtained from a generalized indirect Fourier transformation (GIFT) technique in combination with a suitable model for the interparticle structure factor. The interparticle interaction is captured using the rescaled mean spherical approximation (RMSA) closure relation and a Yukawa form of the interaction potential. Further quantification of the geometrical parameters of the micelles was achieved by a complete fit of the SANS data using a prolate ellipsoidal form factor and the RMSA structure factor. The present study shows that PTHC induces a decrease in the fractional charge of the micelles due to adsorption at the micellar surface and consequent growth of the SDS micelles from nearly globular to rodlike as the concentration of PTHC increases.

Effects of an additional conduction band on the singlet-antiferromagnet competition in the periodic Anderson model

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

Hu, Wenjian; Scalettar, Richard T.; Huang, Edwin W.

The competition between antiferromagnetic (AF) order and singlet formation is a central phenomenon of the Kondo and periodic Anderson Hamiltonians and of the heavy fermion materials they describe. In this paper, we explore the effects of an additional conduction band on magnetism in these models, and, specifically, on changes in the AF-singlet quantum critical point (QCP) and the one particle and spin spectral functions. To understand the magnetic phase transition qualitatively, we first carry out a self-consistent mean field theory (MFT). The basic conclusion is that, at half filling, the coupling to the additional band stabilizes the AF phase tomore » larger f d hybridization V in the PAM. We also explore the possibility of competing ferromagnetic phases when this conduction band is doped away from half filling. Here, we next employ quantum Monte Carlo (QMC) which, in combination with finite size scaling, allows us to evaluate the position of the QCP using an exact treatment of the interactions. This approach confirms the stabilization of AF order, which occurs through an enhancement of the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction. QMC results for the spectral function A (q,ω) and dynamic spin structure factor χ (q,ω) yield additional insight into the AF-singlet competition and the low temperature phases.« less

Effects of an additional conduction band on the singlet-antiferromagnet competition in the periodic Anderson model

DOE PAGES

Hu, Wenjian; Scalettar, Richard T.; Huang, Edwin W.; ...

2017-06-12

The competition between antiferromagnetic (AF) order and singlet formation is a central phenomenon of the Kondo and periodic Anderson Hamiltonians and of the heavy fermion materials they describe. In this paper, we explore the effects of an additional conduction band on magnetism in these models, and, specifically, on changes in the AF-singlet quantum critical point (QCP) and the one particle and spin spectral functions. To understand the magnetic phase transition qualitatively, we first carry out a self-consistent mean field theory (MFT). The basic conclusion is that, at half filling, the coupling to the additional band stabilizes the AF phase tomore » larger f d hybridization V in the PAM. We also explore the possibility of competing ferromagnetic phases when this conduction band is doped away from half filling. Here, we next employ quantum Monte Carlo (QMC) which, in combination with finite size scaling, allows us to evaluate the position of the QCP using an exact treatment of the interactions. This approach confirms the stabilization of AF order, which occurs through an enhancement of the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction. QMC results for the spectral function A (q,ω) and dynamic spin structure factor χ (q,ω) yield additional insight into the AF-singlet competition and the low temperature phases.« less

Testing for departures from additivity in mixtures of perfluoroalkyl acids (PFAAs)

EPA Science Inventory

This study is a follow-up to a paper by Carr, et al. that determined a design structure to optimally test for departures from additivity in a fixed ratio mixture of four perfluoroalkyl acids (PFAAs) using an in vitro transiently-transfected COS- 1 PPARa reporter model with an NHA...

Cardiovascular risk assessment: addition of CKD and race to the Framingham equation

PubMed Central

Drawz, Paul E.; Baraniuk, Sarah; Davis, Barry R.; Brown, Clinton D.; Colon, Pedro J.; Cujyet, Aloysius B.; Dart, Richard A.; Graumlich, James F.; Henriquez, Mario A.; Moloo, Jamaluddin; Sakalayen, Mohammed G.; Simmons, Debra L.; Stanford, Carol; Sweeney, Mary Ellen; Wong, Nathan D.; Rahman, Mahboob

2012-01-01

Background/Aims The value of the Framingham equation in predicting cardiovascular risk in African Americans and patients with chronic kidney disease (CKD) is unclear. The purpose of the study was to evaluate whether the addition of CKD and race to the Framingham equation improves risk stratification in hypertensive patients. Methods Participants in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) were studied. Those randomized to doxazosin, age greater than 74 years, and those with a history of coronary heart disease (CHD) were excluded. Two risk stratification models were developed using Cox proportional hazards models in a two-thirds developmental sample. The first model included the traditional Framingham risk factors. The second model included the traditional risk factors plus CKD, defined by eGFR categories, and stratification by race (Black vs. Non-Black). The primary outcome was a composite of fatal CHD, nonfatal MI, coronary revascularization, and hospitalized angina. Results There were a total of 19,811 eligible subjects. In the validation cohort, there was no difference in C-statistics between the Framingham equation and the ALLHAT model including CKD and race. This was consistent across subgroups by race and gender and among those with CKD. One exception was among Non-Black women where the C-statistic was higher for the Framingham equation (0.68 vs 0.65, P=0.02). Additionally, net reclassification improvement was not significant for any subgroup based on race and gender, ranging from −5.5% to 4.4%. Conclusion The addition of CKD status and stratification by race does not improve risk prediction in high-risk hypertensive patients. PMID:23194494

Additive hazards regression and partial likelihood estimation for ecological monitoring data across space.

PubMed

Lin, Feng-Chang; Zhu, Jun

2012-01-01

We develop continuous-time models for the analysis of environmental or ecological monitoring data such that subjects are observed at multiple monitoring time points across space. Of particular interest are additive hazards regression models where the baseline hazard function can take on flexible forms. We consider time-varying covariates and take into account spatial dependence via autoregression in space and time. We develop statistical inference for the regression coefficients via partial likelihood. Asymptotic properties, including consistency and asymptotic normality, are established for parameter estimates under suitable regularity conditions. Feasible algorithms utilizing existing statistical software packages are developed for computation. We also consider a simpler additive hazards model with homogeneous baseline hazard and develop hypothesis testing for homogeneity. A simulation study demonstrates that the statistical inference using partial likelihood has sound finite-sample properties and offers a viable alternative to maximum likelihood estimation. For illustration, we analyze data from an ecological study that monitors bark beetle colonization of red pines in a plantation of Wisconsin.

Modeller's attitude in catchment modelling: a comparative study

NASA Astrophysics Data System (ADS)

Battista Chirico, Giovanni

2010-05-01

Ten modellers have been invited to predict, independently from each other, the discharge of the artificial Chicken Creek catchment in North-East Germany for simulation period of three years, providing them only soil texture, terrain and meteorological data. No data concerning the discharge or other sources of state variables and fluxes within the catchment have been provided. Modellers had however the opportunity to visit the experimental catchment and inspect areal photos of the catchments since its initial development stage. This study has been a unique comparative study focussing on how different modellers deal with the key issues in predicting the discharge in ungauged catchments: 1) choice of the model structure; 2) identification of model parameters; 3) identification of model initial and boundary conditions. The first general lesson learned during this study was that the modeller is just part of the entire modelling process and has a major bearing on the model results, particularly in ungauged catchments where there are more degrees of freedom in making modelling decisions. Modellers' attitudes during the stages of the model implementation and parameterisation have been deeply influenced by their own experience from previous modelling studies. A common outcome was that modellers have been mainly oriented to apply process-based models able to exploit the available data concerning the physical properties of the catchment and therefore could be more suitable to cope with the lack of data concerning state variables or fluxes. The second general lesson learned during this study was the role of dominant processes. We believed that the modelling task would have been much easier in an artificial catchment, where heterogeneity were expected to be negligible and processes simpler, than in catchments that have evolved over a longer time period. The results of the models were expected to converge, and this would have been a good starting point to proceed for a model

Deschutes estuary feasibility study: hydrodynamics and sediment transport modeling

USGS Publications Warehouse

George, Douglas A.; Gelfenbaum, Guy; Lesser, Giles; Stevens, Andrew W.

2006-01-01

- Provide the completed study to the CLAMP Steering Committee so that a recommendation about a long-term aquatic environment of the basin can be made. The hydrodynamic and sediment transport modeling task developed a number of different model simulations using a process-based morphological model, Delft3D, to help address these goals. Modeling results provide a qualitative assessment of estuarine behavior both prior to dam construction and after various post-dam removal scenarios. Quantitative data from the model is used in the companion biological assessment and engineering design components of the overall study. Overall, the modeling study found that after dam removal, tidal and estuarine processes are immediately restored, with marine water from Budd Inlet carried into North and Middle Basin on each rising tide and mud flats being exposed with each falling tide. Within the first year after dam removal, tidal processes, along with the occasional river floods, act to modify the estuary bed by redistributing sediment through erosion and deposition. The morphological response of the bed is rapid during the first couple of years, then slows as a dynamic equilibrium is reached within three to five years. By ten years after dam removal, the overall hydrodynamic and morphologic behavior of the estuary is similar to the pre-dam estuary, with the exception of South Basin, which has been permanently modified by human activities. In addition to a qualitative assessment of estuarine behavior, process-based modeling provides the ability address specific questions to help to inform decision-making. Considering that predicting future conditions of a complex estuarine environment is wrought with uncertainties, quantitative results in this report are often expressed in terms of ranges of possible outcomes.