Relevant bibliographies by topics / PH Weibull model

Academic literature on the topic 'PH Weibull model'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "PH Weibull model"

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Tsai, Bor-Wen, John T. Harvey, and Carl L. Monismith. "Application of Weibull Theory in Prediction of Asphalt Concrete Fatigue Performance." Transportation Research Record: Journal of the Transportation Research Board 1832, no. 1 (January 2003): 121–30. http://dx.doi.org/10.3141/1832-15.

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The objectives are to present the feasibility of utilizing the Weibull proportional hazards (PH) model and the Weibull accelerated failure time model of survival analysis to predict in situ pavement fatigue performance from laboratory fatigue test results. A set of WesTrack temperature sensitivity fatigue tests is used as an example to demonstrate how the Weibull PH model works. An example utilizing the deflection data from a heavy vehicle simulator test is given to verify the feasibility of the failure time model. The relationship between mode factor and controlled-deformation fatigue test is discussed using the same example. The Weibull theory approach has potential for use in recursive mechanistic-empirical design procedures.
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BLACK, D. GLENN, X. PHILIP YE, FEDERICO HARTE, and P. MICHAEL DAVIDSON. "Thermal Inactivation of Escherichia coli O157:H7 When Grown Statically or Continuously in a Chemostat." Journal of Food Protection 73, no. 11 (November 1, 2010): 2018–24. http://dx.doi.org/10.4315/0362-028x-73.11.2018.

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The objective of this study was to determine if survivor curves for heat-inactivated Escherichia coli O157:H7 were affected by the physiological state of the cells relative to growth conditions and pH of the heating menstruum. A comparison was made between the log-linear model and non–log-linear Weibull approach. Cells were grown statically in aerobic culture tubes or in an aerobic chemostat in tryptic soy broth (pH 7.2). The heating menstruum was unbuffered peptone or phosphate buffer (pH 7.0). Thermal inactivation was carried out at 58, 59, 60, and 61°C, and recovery was on a nonselective medium. Longer inactivation times for statically grown cells indicated potential stress adaptation. This was more prevalent at 58°C. Shape response was also significantly different, with statically grown cells exhibiting decreasing thermal resistance over time and chemostat cells showing the opposite effect. Buffering the heating menstruum to ca. pH 7 resulted in inactivation curves that showed less variability or scatter of data points. Time to specific log reduction values (td) for the Weibull model were conservative relative to the log-linear model depending upon the stage of reduction. The Weibull model offered the most accurate fit of the data in all cases, especially considering the log-linear model is equivalent to the Weibull model with a fixed shape factor of 1. The determination of z-value for the log-linear model showed a strong correlation between log D-value and process temperature. Correlations for the Weibull model parameters (log δand log p) versus process temperature were not statistically significant.
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Mestre, Luis, David Allison, Keisuke Ejima, Nianjun Liu, and Greg Pavela. "Determining an Appropriate Statistical Model when Assessing the Association between Obesity and Mortality." Current Developments in Nutrition 6, Supplement_1 (June 2022): 38. http://dx.doi.org/10.1093/cdn/nzac047.038.

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Abstract Objectives To determine a statistical model appropriate to assess the association between Obesity and mortality using epidemiological data. We hypothesized that the model with the lowest AIC, BIC, and lowest Sobol's Indices is the appropriate model, compared to the others, to assess the association between obesity and mortality. Methods The datasets used were the National Child Development Study, the Health Retirement Study, the National Health Interview Survey, and the National Health and Nutrition Examination Survey. The statistical models compared were the Cox PH Model and the AFT Model. For the AFT Model, we used the Weibull Distribution, Lognormal Distribution, and Exponential Distribution. Body mass index (BMI) was used as a proxy for obesity, the exposure of interest. Mortality, the event of interest, was calculated using age and a death indicator of the participants. Covariates were sex, socioeconomic status (SES), education, smoking status, drinking status. The interactions were between BMI and SES, BMI and Sex, BMI and Smoking Status. Results The results of the NCDS dataset indicated that the Cox PH Model has an AIC of 11528.81, BIC of 11611.81 without interactions, an AIC of 11502.04, and BIC of 11640.36 with interaction. The Cox PH model has the highest AIC and BIC regardless of the inclusion of interactions compared to the AFT Models. The AFT model with a Weibull distribution had the lowest AIC and BIC (without interaction: 8367.61 and 8521.30, respectively and with interaction: 8346.29 and 8592.19, respectively). The Sobol's Indices for the models, without interaction, were close to zero for all covariates except education, where all models were close to one. However, with interactions, the Sobol's Indices of the education covariate decreases for all AFT Models though the Cox PH Model remains the highest and without change. Conclusions Given our sample and specified model, the AFT model with a Weibull distribution appeared to fit the data better relative to the Cox PH Model or the other AFT Models. The Cox PH model is more sensitive to interactions than the AFT Models. Funding Sources National Institute of Aging (NIA): 3R01AG057703-02S1
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Koseki, Shige, Yasuko Mizuno, and Itaru Sotome. "Modeling of Pathogen Survival during Simulated Gastric Digestion." Applied and Environmental Microbiology 77, no. 3 (December 3, 2010): 1021–32. http://dx.doi.org/10.1128/aem.02139-10.

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ABSTRACTThe objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogensListeria monocytogenes,Escherichia coliO157:H7, andSalmonellaspp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens.
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Dufort, Evann L., Jonathan Sogin, Mark R. Etzel, and Barbara H. Ingham. "Inactivation Kinetics of Pathogens during Thermal Processing in Acidified Broth and Tomato Purée (pH 4.5)." Journal of Food Protection 80, no. 12 (November 1, 2017): 2014–21. http://dx.doi.org/10.4315/0362-028x.jfp-17-147.

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ABSTRACT Thermal inactivation kinetics for single strains of Shiga toxin–producing Escherichia coli (STEC), Listeria monocytogenes, and Salmonella enterica were measured in acidified tryptic soy broth (TSB; pH 4.5) heated at 54°C. Inactivation curves also were measured for single-pathogen five-strain cocktails of E. coli O157:H7, L. monocytogenes, and S. enterica heated in tomato purée (pH 4.5) at 52, 54, 56, and 58°C. Inactivation curves were fit using log-linear and nonlinear (Weibull) models. The Weibull model yields the time for a 5-log reduction (t*) and a curve shape parameter (β). Decimal reduction times (D-values) and thermal resistance constants (z-values) from the two models were compared by defining t* = 5D* for the Weibull model. When the log-linear and Weibull models match at the 5-log reduction time, then t* = 5D* = 5D and D = D*. In 18 of 20 strains heated in acidified TSB, D and D* for the two models were not significantly different, although nonlinearity was observed in 35 of 60 trials. Similarly, in 51 of 52 trials for pathogen cocktails heated in tomato purée, D and D* were not significantly different, although nonlinearity was observed in 31% of trials. At a given temperature, D-values for S. enterica << L. monocytogenes < E. coli O157:H7 in tomato purée (pH 4.5). When using the two models, z-values calculated from the D-values were not significantly different for a given pathogen. Across all pathogens, z-values for E. coli O157:H7 and S. enterica were not different but were significantly lower than the z-values for L. monocytogenes. These results are useful for supporting process filings for tomato-based acidified food products with pH 4.5 and below and are relevant to small processors of tomato-based acidified canned foods who do not have the resources to conduct research on and validate pathogen lethality.
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Zhang, Zedi, Yuhua Lei, Xiaohong Yang, Nana Shi, Lina Geng, Shuping Wang, Jianjun Zhang, and Shikao Shi. "High drug-loading system of hollow carbon dots–doxorubicin: preparation, in vitro release and pH-targeted research." Journal of Materials Chemistry B 7, no. 13 (2019): 2130–37. http://dx.doi.org/10.1039/c9tb00032a.

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Hosein, Althea M., Frederick Breidt, and Charles E. Smith. "Modeling the Effects of Sodium Chloride, Acetic Acid, and Intracellular pH on Survival ofEscherichia coliO157:H7." Applied and Environmental Microbiology 77, no. 3 (November 29, 2010): 889–95. http://dx.doi.org/10.1128/aem.02136-10.

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ABSTRACTMicrobiological safety has been a critical issue for acid and acidified foods since it became clear that acid-tolerant pathogens such asEscherichia coliO157:H7 can survive (even though they are unable to grow) in a pH range of 3 to 4, which is typical for these classes of food products. The primary antimicrobial compounds in these products are acetic acid and NaCl, which can alter the intracellular physiology ofE. coliO157:H7, leading to cell death. For combinations of acetic acid and NaCl at pH 3.2 (a pH value typical for non-heat-processed acidified vegetables), survival curves were described by using a Weibull model. The data revealed a protective effect of NaCl concentration on cell survival for selected acetic acid concentrations. The intracellular pH of anE. coliO157:H7 strain exposed to acetic acid concentrations of up to 40 mM and NaCl concentrations between 2 and 4% was determined. A reduction in the intracellular pH was observed for increasing acetic acid concentrations with an external pH of 3.2. Comparing intracellular pH with Weibull model predictions showed that decreases in intracellular pH were significantly correlated with the corresponding times required to achieve a 5-log reduction in the number of bacteria.
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Sharma, Reema, Richa Srivastava, and Satyanshu K. Upadhyay. "A Hierarchical Bayes Analysis and Comparison of PH Weibull and PH Exponential Models for One-Shot Device Testing Experiment." International Journal of Reliability, Quality and Safety Engineering 28, no. 05 (July 30, 2021): 2150036. http://dx.doi.org/10.1142/s0218539321500364.

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The one-shot devices are highly reliable and, therefore, accelerated life tests are often employed to perform the experiments on such devices. Obviously, in the process, some covariates are introduced. This paper considers the proportional hazards model to observe the effect of covariates on the failure rates under the assumption of two commonly used models, namely the exponential and the Weibull for the lifetimes. The Bayes implementation is proposed using the hybridization of Gibbs and Metropolis algorithms that routinely extend to missing data situations as well. The entertained models are compared using the Bayesian and deviance information criteria and the expected posterior predictive loss criterion. Finally, the results based on two real data examples are given as an illustration.
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Jajang, Jajang, Raden Ninditya Ghina Ashfahani, Agustini Tripena Br.Sb, and Nunung Nurhayati. "MODEL SURVIVAL SEMIPARAMETRIK DAN PARAMETRIK UNTUK DATA DEMAM BERDARAH DENGUE (DBD) DI RSUD KABUPATEN CIAMIS TAHUN 2020." JST (Jurnal Sains dan Teknologi) 11, no. 2 (August 15, 2022): 419–25. http://dx.doi.org/10.23887/jstundiksha.v11i2.43493.

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The research is about the best survival analysis model used for patients with Dengue Hemorrhagic Fever (DHF) at Ciamis Hospital in 2020. The purpose of this research is to identify the factors that influence the rate of cure for DHF at Ciamis Hospital in 2020. The method used is survival analysis. Furthermore, the parametric model used Weibull PH, whereas the semiparametric model used Cox PH regression. The result of the analysis showed that the best model obtained was the semiparametric Cox PH regression model, with significant factors including age, Pack Cell Volume (PCV), hemoglobin, White Blood Cell (WBC), and body temperature.
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HU, XIAOPEI, PARAMESWARAKUMAR MALLIKARJUNAN, JAHEON KOO, LINDA S. ANDREWS, and MICHAEL L. JAHNCKE. "Comparison of Kinetic Models To Describe High Pressure and Gamma Irradiation Used To Inactivate Vibrio vulnificus and Vibrio parahaemolyticus Prepared in Buffer Solution and in Whole Oysters." Journal of Food Protection 68, no. 2 (February 1, 2005): 292–95. http://dx.doi.org/10.4315/0362-028x-68.2.292.

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Comparisons of different models in inactivation kinetics were conducted on data obtained from high-pressure and gamma-irradiation processing. Vibrio vulnificus (MO-624) and Vibrio parahaemolyticus (O3:K6 TX-2103) suspended in phosphate-buffered saline (pH 7.4, 107 CFU/ml) were exposed to pressures from 207 to 379 MPa for 1 to 20 min. Inoculated whole oysters (106 CFU/g) were exposed to pressure from 276 to 379 MPa for 1 to 15 min. Pure cultures and inoculated oysters (106 CFU/g) also were irradiated (gamma irradiation) at doses of less than 3 kGy. Four mathematical models, the Bigelow model, Arrhenius equation, Fermi equation, and Weibull frequency distributions, were applied to microbial survival data, and performances of the different kinetic models were compared. Weibull frequency distributions can predict the high-pressure inactivation of Vibrio spp. with more accuracy in both pure cultures and inoculated oyster samples. The Fermi model provided a better description of gamma-irradiation inactivation kinetics compared with the traditional Bigelow model.
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Conference papers on the topic "PH Weibull model"

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Tronskar, Jens P., Zhang Li, and John D. Edwards. "Probabilistic Integrity Assessment of Pipelines and Pressure Vessels With Localized Corrosion." In ASME 2005 24th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2005. http://dx.doi.org/10.1115/omae2005-67543.

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The acceptability of localized corrosion for pipelines in service is discussed and the methodology for probabilistic assessment of corrosion damage using the 2004 revision of Det Norske Veritas document DNV-RP-F101 is presented with regard to predicting the remaining life of onshore, offshore pipelines and also pressure vessels for the oil and gas industry. Capacity assessment of corrosion defects in pipelines and pressure vessels is a challenge for the industry, and has resulted in several methods and codes in the recent years. The methods include ASME B31G for pipelines and other standards and recommended practices that can be applied for pipelines as well as pressure vessels such as BS7910 Annex G and API 579. In 1999 DNV issued a recommended practice for the assessment of corroded pipelines, DNV-RP-F101, which was developed in co-operation with the pipeline industry. A revision of this document was issued in October 2004. The latest revision provides guidelines for probabilistic assessment of the pipeline reliability and remaining life. Pipeline corrosion is often of localized nature and depends on many factors such as fluid composition and partial pressures, temperature, pH, flow rate and efficiency of corrosion inhibition. These factors may not be easy to quantify with great certainty and a probabilistic approach is particularly justified. An approach is presented in this paper where the actual measured corrosion damage is fitted to an extreme value distribution. The future corrosion rate distribution for internal CO2 corrosion is predicted using the latest de Waard and Milliams model and an inhibitor distribution, to predict the corrosion of each pipeline segment. An Gumbel type extreme value approach is applied to estimate the present condition and the local corrosion flaw distribution that may cause a leak of the pipeline in the future. The future corrosion is estimated using the anticipated future operating conditions of the pipeline to predict the corrosion rate distribution expressed in terms of a Weibull distribution. The paper highlights three cases as examples where the approach has been applied for assessing the probability of failure and reliability during service of two offshore pipelines carrying oil and gas with wet CO2, and one stainless steel pressure vessel in a process plant occasionally exposed to trace amounts seawater originating from leaking heat exchangers.
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