The Experts below are selected from a list of 1765860 Experts worldwide ranked by ideXlab platform
Virendra M Puri - One of the best experts on this subject based on the ideXlab platform.
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Modeling the inactivation of salmonella typhimurium listeria monocytogenes and salmonella enteritidis on poultry products exposed to pulsed uv light
Journal of Food Protection, 2012Co-Authors: Nene M. Keklik, Virendra M Puri, Paul Heinz HeinemannAbstract:Pulsed UV light inactivation of Salmonella Typhimurium on unpackaged and vacuum-packaged chicken breast, Listeria monocytogenes on unpackaged and vacuum-packaged chicken frankfurters, and Salmonella Enteritidis on shell eggs was explained by Log-Linear and Weibull Models using inactivation data from previous studies. This study demonstrated that the survival curves of Salmonella Typhimurium and L. monocytogenes were nonlinear exhibiting concavity. The Weibull Model was more successful than the Log-Linear Model in estimating the inactivations for all poultry products evaluated, except for Salmonella Enteritidis on shell eggs, for which the survival curve was sigmoidal rather than concave, and the use of the Weibull Model resulted in slightly better fit than the Log-Linear Model. The analyses for the goodness of fit and performance of the Weibull Model produced root mean square errors of 0.059 to 0.824, percent root mean square errors of 3.105 to 21.182, determination coefficients of 0.747 to 0.989, slopes ...
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Modeling the inactivation of Salmonella Typhimurium, Listeria monocytogenes, and Salmonella Enteritidis on poultry products exposed to pulsed UV-light
2011 Louisville Kentucky August 7 - August 10 2011, 2011Co-Authors: Nene M. Keklik, Ali Demirci, Virendra M Puri, Paul Heinz HeinemannAbstract:Inactivation of Salmonella Typhimurium on unpackaged and vacuum-packaged chicken breast, Listeria monocytogenes on unpackaged and vacuum-packaged chicken frankfurters, and Salmonella Enteritidis on egg shells via pulsed UV-light were explained by Log-Linear and Weibull Models using inactivation data from previous studies. This study demonstrated that the survival curves of S. Typhimurium and L. monocytogenes were non-linear exhibiting concavity, and the Weibull Model was more successful than the Log-Linear Model in estimating the inactivation for all poultry products evaluated, except for S. Enteritidis on shell-eggs, for which the survival curve was sigmoidal rather than concave, and the use of the Weibull Model resulted in slightly better fit than the Log-Linear Model. The goodness-of-fit of the Weibull Model parameters produced RMSEs of 0.06-0.82, % RMSEs of 3.1-21.2, determination coefficients of 0.75-0.99, and slopes of 0.84-0.95. Overall, this study suggests that the survival curves of pathogens on poultry products exposed to pulsed UV-light are non-linear, and the Weibull Model can generally be a useful tool to describe the inactivation patterns for pathogenic microorganisms affiliated with poultry products.
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Modeling the inactivation of escherichia coli o157 h7 and salmonella enterica on raspberries and strawberries resulting from exposure to ozone or pulsed uv light
Journal of Food Engineering, 2008Co-Authors: Katherine L. Bialka, Ali Demirci, Virendra M PuriAbstract:Inactivation data for Escherichia coli O157:H7 and Salmonella enterica on raspberries and strawberries resulting from treatment with gaseous ozone, aqueous ozone, or pulsed UV-light were used to construct inactivation Models; a Log-Linear Model (based on first-order kinetics) and a Weibull Model were developed. Initial analysis indicated that survival curves were non-linear and that the Log-Linear Model failed to accurately estimate the inactivations in most instances. The Weibull Model more accurately estimated the inactivation and the concavity exhibited in the survival curves. Validation of the Weibull Model produced correlation coefficients of 0.83–0.99 and slopes of 0.76–1.26. The results presented in this study indicated that first-order kinetics are not suitable for the estimation of microbial inactivation on berries treated with ozone or pulsed UV-light, but that the Weibull Model can be successfully used to estimate the reductions of E. coli O157:H7 and Salmonella enterica on raspberries and strawberries.
Paul Heinz Heinemann - One of the best experts on this subject based on the ideXlab platform.
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Modeling the inactivation of salmonella typhimurium listeria monocytogenes and salmonella enteritidis on poultry products exposed to pulsed uv light
Journal of Food Protection, 2012Co-Authors: Nene M. Keklik, Virendra M Puri, Paul Heinz HeinemannAbstract:Pulsed UV light inactivation of Salmonella Typhimurium on unpackaged and vacuum-packaged chicken breast, Listeria monocytogenes on unpackaged and vacuum-packaged chicken frankfurters, and Salmonella Enteritidis on shell eggs was explained by Log-Linear and Weibull Models using inactivation data from previous studies. This study demonstrated that the survival curves of Salmonella Typhimurium and L. monocytogenes were nonlinear exhibiting concavity. The Weibull Model was more successful than the Log-Linear Model in estimating the inactivations for all poultry products evaluated, except for Salmonella Enteritidis on shell eggs, for which the survival curve was sigmoidal rather than concave, and the use of the Weibull Model resulted in slightly better fit than the Log-Linear Model. The analyses for the goodness of fit and performance of the Weibull Model produced root mean square errors of 0.059 to 0.824, percent root mean square errors of 3.105 to 21.182, determination coefficients of 0.747 to 0.989, slopes ...
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Modeling the inactivation of Salmonella Typhimurium, Listeria monocytogenes, and Salmonella Enteritidis on poultry products exposed to pulsed UV-light
2011 Louisville Kentucky August 7 - August 10 2011, 2011Co-Authors: Nene M. Keklik, Ali Demirci, Virendra M Puri, Paul Heinz HeinemannAbstract:Inactivation of Salmonella Typhimurium on unpackaged and vacuum-packaged chicken breast, Listeria monocytogenes on unpackaged and vacuum-packaged chicken frankfurters, and Salmonella Enteritidis on egg shells via pulsed UV-light were explained by Log-Linear and Weibull Models using inactivation data from previous studies. This study demonstrated that the survival curves of S. Typhimurium and L. monocytogenes were non-linear exhibiting concavity, and the Weibull Model was more successful than the Log-Linear Model in estimating the inactivation for all poultry products evaluated, except for S. Enteritidis on shell-eggs, for which the survival curve was sigmoidal rather than concave, and the use of the Weibull Model resulted in slightly better fit than the Log-Linear Model. The goodness-of-fit of the Weibull Model parameters produced RMSEs of 0.06-0.82, % RMSEs of 3.1-21.2, determination coefficients of 0.75-0.99, and slopes of 0.84-0.95. Overall, this study suggests that the survival curves of pathogens on poultry products exposed to pulsed UV-light are non-linear, and the Weibull Model can generally be a useful tool to describe the inactivation patterns for pathogenic microorganisms affiliated with poultry products.
Robert G Aykroyd - One of the best experts on this subject based on the ideXlab platform.
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birnbaum saunders spatial Modelling and diagnostics applied to agricultural engineering data
Stochastic Environmental Research and Risk Assessment, 2017Co-Authors: Fabiana Garciapapani, Miguel Angel Uribeopazo, Victor Leiva, Robert G AykroydAbstract:Applications of statistical Models to describe spatial dependence in geo-referenced data are widespread across many disciplines including the environmental sciences. Most of these applications assume that the data follow a Gaussian distribution. However, in many of them the normality assumption, and even a more general assumption of symmetry, are not appropriate. In non-spatial applications, where the data are uni-modal and positively skewed, the Birnbaum–Saunders (BS) distribution has excelled. This paper proposes a spatial Log-Linear Model based on the BS distribution. Model parameters are estimated using the maximum likelihood method. Local influence diagnostics are derived to assess the sensitivity of the estimators to perturbations in the response variable. As illustration, the proposed Model and its diagnostics are used to analyse a real-world agricultural data set, where the spatial variability of phosphorus concentration in the soil is considered—which is extremely important for agricultural management.
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Birnbaum-Saunders spatial Modelling and diagnostics applied to agricultural engineering data
'Springer Science and Business Media LLC', 2017Co-Authors: Garcia-papani F, Robert G AykroydAbstract:Applications of statistical Models to describe spatial dependence in geo-referenced data are widespread across many disciplines including the environmental sciences. Most of these application assume that the data follow a Gaussian distributions. However, in many of them the normality assumption, and even a more general assumption of symmetry, are not appropriate. In non-spatial applications, where the data are uni-modal and positively skewed, the Birnbaum-Saunders distribution has excelled. This paper proposes a spatial Log-Linear Model based in the Birnbaum-Saunders distribution. Model parameters are estimated using the maximum likelihood method. Local influence diagnostics are derived to assess the sensitivity of the estimators to perturbations in the response variable. As illustration, the proposed Model and its diagnostics are used to analyse a real-world agricultural data-set, where the spatial variability of phosphorus concentration in the soil is considered- which is extremely important for agricultural management
Victor Leiva - One of the best experts on this subject based on the ideXlab platform.
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birnbaum saunders spatial Modelling and diagnostics applied to agricultural engineering data
Stochastic Environmental Research and Risk Assessment, 2017Co-Authors: Fabiana Garciapapani, Miguel Angel Uribeopazo, Victor Leiva, Robert G AykroydAbstract:Applications of statistical Models to describe spatial dependence in geo-referenced data are widespread across many disciplines including the environmental sciences. Most of these applications assume that the data follow a Gaussian distribution. However, in many of them the normality assumption, and even a more general assumption of symmetry, are not appropriate. In non-spatial applications, where the data are uni-modal and positively skewed, the Birnbaum–Saunders (BS) distribution has excelled. This paper proposes a spatial Log-Linear Model based on the BS distribution. Model parameters are estimated using the maximum likelihood method. Local influence diagnostics are derived to assess the sensitivity of the estimators to perturbations in the response variable. As illustration, the proposed Model and its diagnostics are used to analyse a real-world agricultural data set, where the spatial variability of phosphorus concentration in the soil is considered—which is extremely important for agricultural management.
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a multivariate log linear Model for birnbaum saunders distributions
IEEE Transactions on Reliability, 2016Co-Authors: Carolina Marchant, Victor Leiva, Francisco Jose A CysneirosAbstract:Univariate Birnbaum-Saunders Models have been widely applied to fatigue studies. Calculation of fatigue life is of great importance in determining the reliability of materials. We propose and derive new multivariate generalized Birnbaum-Saunders regression Models. We use the maximum likelihood method and the EM algorithm to estimate their parameters. We carry out a simulation study to evaluate the performance of the corresponding maximum likelihood estimators. We illustrate the new Models with real-world multivariate fatigue data.
Man Jin - One of the best experts on this subject based on the ideXlab platform.
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likelihood ratio and score tests to test the non inferiority or equivalence of the odds ratio in a crossover study with binary outcomes
Statistics in Medicine, 2016Co-Authors: Man Jin, Judith D GoldbergAbstract:We consider the non-inferiority (or equivalence) test of the odds ratio (OR) in a crossover study with binary outcomes to evaluate the treatment effects of two drugs. To solve this problem, Lui and Chang (2011) proposed both an asymptotic method and a conditional method based on a random effects logit Model. Kenward and Jones (1987) proposed a likelihood ratio test (LRTM ) based on a log linear Model. These existing methods are all subject to Model misspecification. In this paper, we propose a likelihood ratio test (LRT) and a score test that are independent of Model specification. Monte Carlo simulation studies show that, in scenarios considered in this paper, both the LRT and the score test have higher power than the asymptotic and conditional methods for the non-inferiority test; the LRT, score, and asymptotic methods have similar power, and they all have higher power than the conditional method for the equivalence test. When data can be well described by a log linear Model, the LRTM has the highest power among all the five methods (LRTM , LRT, score, asymptotic, and conditional) for both non-inferiority and equivalence tests. However, in scenarios for which a log linear Model does not describe the data well, the LRTM has the lowest power for the non-inferiority test and has inflated type I error rates for the equivalence test. We provide an example from a clinical trial that illustrates our methods. Copyright © 2016 John Wiley & Sons, Ltd.
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Data from: Likelihood Ratio and Score Tests to Test the Non-inferiority (or Equivalence) of the Odds Ratio in a Crossover Study with Binary Outcomes
2016Co-Authors: Man Jin, Judith D GoldbergAbstract:We consider the non-inferiority (or equivalence) test of the odds ratio (OR) in a crossover study with binary outcomes to evaluate the treatment effects of two drugs. To solve this problem, Lui and Chang (2011) proposed both an asymptotic method and a conditional method based on a random effects logit Model. Kenward and Jones (1987) proposed a likelihood ratio test (LRT_M) based on a log linear Model. These existing methods are all subject to Model misspecification. In this paper, we propose a likelihood ratio test (LRT) and a score test that are independent of Model specification. Monte Carlo simulation studies show that, in scenarios considered in this paper, both the LRT and the score test have higher power than the asymptotic and conditional methods for the non-inferiority test; the LRT, score and asymptotic methods have similar power and they all have higher power than the conditional method for the equivalence test. When data can be well described by a log linear Model, the LRT_M has the highest power among all the five methods (LRT_M, LRT, score, asymptotic and conditional) for both non-inferiority and equivalence tests. However, in scenarios for which a log linear Model does not describe the data well, the LRT_M has the lowest power for the non-inferiority test and has inflated type I error rates for the equivalence test. We provide an example from a clinical trial that illustrates our methods
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variable selection in generalized linear Models with canonical link functions
Statistics & Probability Letters, 2005Co-Authors: Man Jin, Yixin Fang, Lincheng ZhaoAbstract:This paper studies a class of AIC-like Model selection criteria for a generalized linear Model with the canonical link. They have the form of , where is the maximized log-likelihood, p is the number of parameters and C is a term depending on the sample size n and satisfying C/n-->0 and as n-->[infinity]. Under suitable conditions, this class of criteria is shown to be strongly consistent. A simulation study was also conducted to assess the finite-sample performance with various choices of C for variable selection in a logit Model and a Log-Linear Model.
