scholarly journals Kinetic and hybrid modelling for yeast astaxanthin production under uncertainty

2021 ◽  
Author(s):  
Fernando Vega‐Ramon ◽  
Xianfeng Zhu ◽  
Thomas R. Savage ◽  
Panagiotis Petsagkourakis ◽  
Keju Jing ◽  
...  
Keyword(s):  
Hybrid Modelling ◽  
Astaxanthin Production

Investigation of a New Approach to Predict Water Quality Extremes with a Case Study of Chemical Determinands in Stream Water

1991 ◽  
Vol 24 (6) ◽  
pp. 25-33
Author(s):  
A. J. Jakeman ◽  
P. G. Whitehead ◽  
A. Robson ◽  
J. A. Taylor ◽  
J. Bai
Keyword(s):  
Water Quality ◽  
Stream Water ◽  
Probability Distributions ◽  
Management Strategies ◽  
Hybrid Modelling ◽  
Trend Model ◽  
Environmental Extremes ◽  
Modelling Approach

The paper illustrates analysis of the assumptions of the statistical component of a hybrid modelling approach for predicting environmental extremes. This shows how to assess the applicability of the approach to water quality problems. The analysis involves data on stream acidity from the Birkenes catchment in Norway. The modelling approach is hybrid in that it uses: (1) a deterministic or process-based description to simulate (non-stationary) long term trend values of environmental variables, and (2) probability distributions which are superimposed on the trend values to characterise the frequency of shorter term concentrations. This permits assessment of management strategies and of sensitivity to climate variables by adjusting the values of major forcing variables in the trend model. Knowledge of the variability about the trend is provided by: (a) identification of an appropriate parametric form of the probability density function (pdf) of the environmental attribute (e.g. stream acidity variables) whose extremes are of interest, and (b) estimation of pdf parameters using the output of the trend model.

scholarly journals Physical and hybrid modelling techniques for earth-air heat exchangers in reducing building energy consumption: Performance, applications, progress, and challenges

Solar Energy ◽  
2021 ◽  
Vol 216 ◽  
pp. 274-294
Author(s):  
S.F. Ahmed ◽  
G. Liu ◽  
M. Mofijur ◽  
A.K. Azad ◽  
M.A. Hazrat ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Heat Exchangers ◽  
Building Energy ◽  
Building Energy Consumption ◽  
Hybrid Modelling ◽  
Modelling Techniques

A green decontamination technology through selective biomineralization of algicidal microorganisms for enhanced astaxanthin production from Haematococcus pluvialis at commercial scale

2021 ◽  
pp. 125121
Author(s):  
Byung Sun Yu ◽  
Min Eui Hong ◽  
Young Joon Sung ◽  
Hong Il Choi ◽  
Won Seok Chang ◽  
...  
Keyword(s):  
Haematococcus Pluvialis ◽  
Commercial Scale ◽  
Astaxanthin Production

scholarly journals Viscosity Model for Nanoparticulate Suspensions Based on Surface Interactions

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2752
Author(s):  
Benedikt Finke ◽  
Clara Sangrós Sangrós Giménez ◽  
Arno Kwade ◽  
Carsten Schilde
Keyword(s):  
Mechanistic Model ◽  
Model Development ◽  
Rheological Behaviour ◽  
Hybrid Modelling ◽  
Shear Rates ◽  
Drag Forces ◽  
Boehmite Nanoparticles ◽  
Data Points ◽  
Two Parameters ◽  
Physical Phenomena

In this paper, a widely mechanistic model was developed to depict the rheological behaviour of nanoparticulate suspensions with solids contents up to 20 wt.%, based on the increase in shear stress caused by surface interaction forces among particles. The rheological behaviour is connected to drag forces arising from an altered particle movement with respect to the surrounding fluid. In order to represent this relationship and to model the viscosity, a hybrid modelling approach was followed, in which mechanistic relationships were paired with heuristic expressions. A genetic algorithm was utilized during model development, by enabling the algorithm to choose among several hard-to-assess model options. By the combination of the newly developed model with existing models for the various physical phenomena affecting viscosity, it can be applied to model the viscosity over a broad range of solids contents, shear rates, temperatures and particle sizes. Due to its mechanistic nature, the model even allows an extrapolation beyond the limits of the data points used for calibration, allowing a prediction of the viscosity in this area. Only two parameters are required for this purpose. Experimental data of an epoxy resin filled with boehmite nanoparticles were used for calibration and comparison with modelled values.

Gibberellic acid‐induced fatty acid metabolism and ABC transporters promote astaxanthin production in Phaffia rhodozyma

2021 ◽  
Author(s):  
Sijiao Liu ◽  
Hong Yi ◽  
Honglei Zhan ◽  
Liang Wang ◽  
Jihui Wang ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Gibberellic Acid ◽  
Fatty Acid Metabolism ◽  
Abc Transporters ◽  
Acid Metabolism ◽  
Phaffia Rhodozyma ◽  
Astaxanthin Production

scholarly journals Hybrid modelling of the RED algorithm in the Julia language

2020 ◽  
Vol 1694 ◽  
pp. 012025
Author(s):  
A M Yu Apreutesey ◽  
A V Korolkova ◽  
D S Kulyabov
Keyword(s):  
Hybrid Modelling

scholarly journals Use Of Deep Learning To Predict Tumor Response To Neoadjuvant Therapy In Pancreatic Adenocarcinoma: Pure And Hybrid Modelling

HPB ◽  
2020 ◽  
Vol 22 ◽  
pp. S38
Author(s):  
M. Watson ◽  
M. Baimas-George ◽  
K. Murphy ◽  
R. Pickens ◽  
D. Iannitti ◽  
...  
Keyword(s):  
Deep Learning ◽  
Neoadjuvant Therapy ◽  
Pancreatic Adenocarcinoma ◽  
Tumor Response ◽  
Hybrid Modelling
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