scholarly journals On the primary model to explain the relation between a rigidity-dependent spectral hardening of proton and helium spectra and

2016 ◽  
Author(s):  
Jing Huang
Keyword(s):  
Primary Model ◽  
Helium Spectra

Nonlinear dispersion hyperbolic models of continuous media

2007 ◽  
Vol 5 ◽  
pp. 273-278
Author(s):  
V.Yu Liapidevskii
Keyword(s):  
Boussinesq Equations ◽  
Nonlinear Dispersion ◽  
Order Of Accuracy ◽  
Flow Models ◽  
Wave Approximation ◽  
Long Wave ◽  
Primary Model ◽  
Nonequilibrium Flows ◽  
Internal Inertia ◽  
Long Wave Approximation

Nonequilibrium flows of an inhomogeneous liquid in channels and pipes are considered in the long-wave approximation. Nonlinear dispersion hyperbolic flow models are derived allowing taking into account the influence of internal inertia during the relative motion of phases upon the structure of nonlinear wave fronts. The asymptotic derivation of dispersion hyperbolic models is shown on the example of classical Boussinesq equations. It is shown that the hyperbolic approximation of the equations has the same order of accuracy as the primary model.

scholarly journals Performance assessment and optimization of a helical Savonius wind turbine by modifying the Bach’s section

2021 ◽  
Vol 3 (8) ◽  
Author(s):  
M. Niyat Zadeh ◽  
M. Pourfallah ◽  
S. Safari Sabet ◽  
M. Gholinia ◽  
S. Mouloodi ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Performance Assessment ◽  
Turbulent Flows ◽  
Power Coefficient ◽  
Speed Ratio ◽  
Tip Speed Ratio ◽  
Basic Model ◽  
Turbine Performance ◽  
Primary Model ◽  
Savonius Wind Turbine

AbstractIn this paper, we attempted to measure the effect of Bach’s section, which presents a high-power coefficient in the standard Savonius model, on the performance of the helical Savonius wind turbine, by observing the parameters affecting turbine performance. Assessment methods based on the tip speed ratio, torque variation, flow field characterizations, and the power coefficient are performed. The present issue was stimulated using the turbulence model SST (k- ω) at 6, 8, and 10 m/s wind flow velocities via COMSOL software. Numerical simulation was validated employing previous articles. Outputs demonstrate that Bach-primary and Bach-developed wind turbine models have less flow separation at the spoke-end than the simple helical Savonius model, ultimately improving wind turbines’ total performance and reducing spoke-dynamic loads. Compared with the basic model, the Bach-developed model shows an 18.3% performance improvement in the maximum power coefficient. Bach’s primary model also offers a 12.4% increase in power production than the initial model’s best performance. Furthermore, the results indicate that changing the geometric parameters of the Bach model at high velocities (in turbulent flows) does not significantly affect improving performance.

scholarly journals Quality tracing in meat supply chains

2014 ◽  
Vol 372 (2017) ◽  
pp. 20130308 ◽  
Author(s):  
Miriam Mack ◽  
Patrick Dittmer ◽  
Marius Veigt ◽  
Mehmet Kus ◽  
Ulfert Nehmiz ◽  
...  
Keyword(s):  
Supply Chains ◽  
Process Analysis ◽  
Decision Support Tool ◽  
Temperature Monitoring ◽  
Support Tool ◽  
Logistics Network ◽  
Primary Model ◽  
Sensory Parameters ◽  
And Storage

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

scholarly journals Alliance of Genome Resources Portal: unified model organism research platform

2019 ◽  
Vol 48 (D1) ◽  
pp. D650-D658 ◽  
Author(s):  
◽  
Julie Agapite ◽  
Laurent-Philippe Albou ◽  
Suzi Aleksander ◽  
Joanna Argasinska ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Model Organism ◽  
Model Organisms ◽  
Data Types ◽  
Primary Model ◽  
Genomic Studies ◽  
Health And Disease ◽  
Extensive Body ◽  
Access To Data ◽  
Model Organism Databases

Abstract The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource.

scholarly journals New Mathematical Modeling Approach for Predicting Microbial Inactivation by High Hydrostatic Pressure

2007 ◽  
Vol 73 (8) ◽  
pp. 2468-2478 ◽  
Author(s):  
Bernadette Klotz ◽  
D. Leo Pyle ◽  
Bernard M. Mackey
Keyword(s):  
Microbial Inactivation ◽  
Inactivation Kinetics ◽  
Published Data ◽  
Model Parameters ◽  
Order Kinetic ◽  
Square Root ◽  
Additional Time ◽  
Decimal Reduction Time ◽  
First Order ◽  
Primary Model

ABSTRACT A new primary model based on a thermodynamically consistent first-order kinetic approach was constructed to describe non-log-linear inactivation kinetics of pressure-treated bacteria. The model assumes a first-order process in which the specific inactivation rate changes inversely with the square root of time. The model gave reasonable fits to experimental data over six to seven orders of magnitude. It was also tested on 138 published data sets and provided good fits in about 70% of cases in which the shape of the curve followed the typical convex upward form. In the remainder of published examples, curves contained additional shoulder regions or extended tail regions. Curves with shoulders could be accommodated by including an additional time delay parameter and curves with tails shoulders could be accommodated by omitting points in the tail beyond the point at which survival levels remained more or less constant. The model parameters varied regularly with pressure, which may reflect a genuine mechanistic basis for the model. This property also allowed the calculation of (a) parameters analogous to the decimal reduction time D and z, the temperature increase needed to change the D value by a factor of 10, in thermal processing, and hence the processing conditions needed to attain a desired level of inactivation; and (b) the apparent thermodynamic volumes of activation associated with the lethal events. The hypothesis that inactivation rates changed as a function of the square root of time would be consistent with a diffusion-limited process.

scholarly journals Growth of Listeria monocytogenes in Thawed Frozen Foods

2017 ◽  
Vol 80 (3) ◽  
pp. 447-453 ◽  
Author(s):  
Ai Kataoka ◽  
Hua Wang ◽  
Philip H. Elliott ◽  
Richard C. Whiting ◽  
Melinda M. Hayman
Keyword(s):  
Growth Rate ◽  
Listeria Monocytogenes ◽  
Growth Rates ◽  
Storage Temperature ◽  
Growth Parameters ◽  
Quadratic Model ◽  
Lag Phase ◽  
Frozen Foods ◽  
Phase Duration ◽  
Primary Model

ABSTRACT The growth characteristics of Listeria monocytogenes inoculated onto frozen foods (corn, green peas, crabmeat, and shrimp) and thawed by being stored at 4, 8, 12, and 20°C were investigated. The growth parameters, lag-phase duration (LPD) and exponential growth rate (EGR), were determined by using a two-phase linear growth model as a primary model and a square root model for EGR and a quadratic model for LPD as secondary models, based on the growth data. The EGR model predictions were compared with growth rates obtained from the USDA Pathogen Modeling Program, calculated with similar pH, salt percentage, and NaNO2 parameters, at all storage temperatures. The results showed that L. monocytogenes grew well in all food types, with the growth rate increasing with storage temperature. Predicted EGRs for all food types demonstrated the significance of storage temperature and similar growth rates among four food types. The predicted EGRs showed slightly slower rate compared with the values from the U.S. Department of Agriculture Pathogen Modeling Program. LPD could not be accurately predicted, possibly because there were not enough sampling points. These data established by using real food samples demonstrated that L. monocytogenes can initiate growth without a prolonged lag phase even at refrigeration temperature (4°C), and the predictive models derived from this study can be useful for developing proper handling guidelines for thawed frozen foods during production and storage.

Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans

2017 ◽  
Vol 81 (2) ◽  
pp. 308-315 ◽  
Author(s):  
Vijay K. Juneja ◽  
Abhinav Mishra ◽  
Abani K. Pradhan
Keyword(s):  
Bacillus Cereus ◽  
Growth Rates ◽  
Linear Models ◽  
Growth Models ◽  
Maximum Growth ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Growth Data ◽  
Three Phase ◽  
Primary Model

ABSTRACT Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (80°C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol–egg yolk–polymyxin agar and incubating at 30°C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination (R2), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between −0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans.

scholarly journals Effect of food matrix type on growth characteristics and hemolysin production of Vibrio alginolyticus

2020 ◽  
Author(s):  
Xiaojun Hu ◽  
Rundong Wang ◽  
Yijia Deng ◽  
Qi Deng ◽  
Zhijia Fang ◽  
...  
Keyword(s):  
Freshwater Fish ◽  
Goodness Of Fit ◽  
Gompertz Model ◽  
Food Matrix ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Primary Model ◽  
Thermostable Direct Hemolysin ◽  
Effect Of Food ◽  
Modified Gompertz Model

Abstract Background: The growth and hemolysin production of V. alginolyticus at 30 °C in briny Tilapia , shrimp, scallop, oyster, pork, chicken, freshwater fish and egg fried rice were investigated. Bacterial counts were enumerated by plate counting. Hemolysin production was evaluated by blood agar and hemolytic titer tests. Results: Based on the goodness of fit primary model statistics (R 2 , MSE, BF, AF), the modified Gompertz model was a better fit to V. alginolyticus growth in foods than the logistic model. Growth kinetic parameters of V. alginolyticus displayed a higher μ max and shorter λ in briny Tilapia > shrimp > freshwater fish > egg fried rice > scallop > oyster > chicken > pork. It was notable that the V. alginolyticus counts were similar at the stationary phase, with no significant growth behavior difference between raw and cooked foods. However, higher thermostable direct hemolysin activity and hemolytic titer were observed in briny Tilapia > egg fried rice > shrimp > freshwater fish > chicken > scallop > oyster > pork. Conclusion: V. alginolyticus growth was good in all food matrix types tested. Contrary to current belief, V. alginolyticus displayed a higher hemolytic activity in some non-seafoods (freshwater fish, egg fried rice and chicken) than in scallop or oyster. This is the first report of growth and toxicity of V. alginolyticus in non-seafood. This finding will significantly improve the accuracy of microbial risk assessment of V. alginolyticus in different food matrices especially during warmer climatic periods when it is most prevalent.

scholarly journals Prediction of growth kinetics of Pseudomonas spp. in meat products under isothermal and non-isothermal storage conditions

2021 ◽  
Vol 7 (3) ◽  
pp. 194-202
Author(s):  
Fatih Tarlak
Keyword(s):  
Goodness Of Fit ◽  
Storage Temperature ◽  
Food Products ◽  
Storage Conditions ◽  
Chicken Meat ◽  
Lag Phase ◽  
Phase Duration ◽  
Pseudomonas Spp ◽  
Primary Model ◽  
One Step

The main objective of the present study was to develop and validate a new alternative modelling method to predict the shelf-life of food products under non-isothermal storage conditions. The bacterial growth data of the Pseudomonas spp. was extracted from published studies conducted for aerobically-stored fish, pork and chicken meat and described with two-step and one-step modelling approaches employing different primary models (the modified Gompertz, logistic, Baranyi and Huang models) under isothermal storage temperatures. Temperature dependent kinetic parameters (maximum specific growth rate ‘µmax’ and lag phase duration ‘λ’) were described as a function of storage temperature via the Ratkowsky model integrated with each primary model. The Huang model based on the one-step modelling approach yielded the best goodness of fit results (RMSE = 0.451 and adjusted-R2 = 0.942) for all food products at isothermal storage conditions, therefore, was also used to check it’s the prediction capability under non-isothermal storage conditions. The differential form of the Huang model provided satisfactorily statistical indexes (1.075 > Bf > 1.014 and 1.080 > Af > 1.047) indicating reliably being able to use to describe the growth behaviour of Pseudomonas spp. in fish, pork and chicken meat subjected to non-isothermal storage conditions.

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