scholarly journals Алгоритмическое и информационное обеспечение разработки готовых лекарственных форм (ГЛФ) лекарственных средств в твердой форме

2021 ◽  
Vol 70 (1) ◽  
pp. 29-37
Author(s):  
Корнюшко В.Ф. ◽  
О.М. Николаева ◽  
Биглов Р.Р. ◽  
К.Ю. Колыбанов ◽  
О.А. Филоретова
Keyword(s):  
Regression Models ◽  
Online Algorithm ◽  
Quality By Design ◽  
Informational Support ◽  
Design Quality ◽  
Pharmaceutical Development ◽  
Simulation And Optimization ◽  
Block Scheme ◽  
Solid Form ◽  
Selection Of

The article discusses the problem of creating an algorithmic and informational support for the pharmaceutical development of ready-made medicines (GLF) medicines in solid form. For the system implementation of the algorithms for the development of GLF on the basis of the principle of QbD (quality-by-design - quality planned during development) it is proposed to apply the methodology of system design based on the principle (diagrams) of Demming. The algorithms for modeling and optimizing the selection of the technology platform for the pharmaceutical development of GLF medicines in solid form are given. The block scheme of the developed algorithm of the simulation and optimization process based on multi-tissue regression models and the online algorithm of optimization of Huka-Jeeves is presented. Testing of the developed algorithmic and software on the example of the development of the drug diphenhydramine.

Optimization of integrated fuzzy decision tree and regression models for selection of oil spill response method in the Arctic

2021 ◽  
Vol 213 ◽  
pp. 106676
Author(s):  
Saeed Mohammadiun ◽  
Guangji Hu ◽  
Abdorreza Alavi Gharahbagh ◽  
Reza Mirshahi ◽  
Jianbing Li ◽  
...  
Keyword(s):  
Decision Tree ◽  
Oil Spill ◽  
Regression Models ◽  
The Arctic ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Oil Spill Response ◽  
Response Method ◽  
Selection Of

scholarly journals Genotypic parameters for egg production in pure breed hens by using random regression model

2017 ◽  
Vol 47 (5) ◽  
Author(s):  
Priscila Becker Ferreira ◽  
Paulo Roberto Nogara Rorato ◽  
Fernanda Cristina Breda ◽  
Vanessa Tomazetti Michelotti ◽  
Alexandre Pires Rosa ◽  
...  
Keyword(s):  
Regression Model ◽  
Regression Models ◽  
Egg Production ◽  
Random Regression ◽  
Broad Sense Heritability ◽  
Residual Matrix ◽  
Random Regression Model ◽  
Residual Covariance ◽  
Genotypic Correlations ◽  
Selection Of

ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.

Selection of Mixed Refrigerant for CBM Liquefaction System and its Optimization Analysis

2012 ◽  
Vol 443-444 ◽  
pp. 193-197
Author(s):  
Q.H. Fan ◽  
H.Y. Li ◽  
L.X. Jia ◽  
Q.H. Fan ◽  
Yi Min Shao ◽  
...  
Keyword(s):  
Mole Fraction ◽  
Heat Exchangers ◽  
Molar Fraction ◽  
Small Scale ◽  
Optimization Analysis ◽  
Mixture Ratio ◽  
Key Technology ◽  
Simulation And Optimization ◽  
Liquefaction Plant ◽  
Selection Of

In the mixed refrigerant cycle, the key technology is the choosing of the mixed refrigerant and its optimization mixture ratio. Based on a small-scale CBM liquefaction system LNG5, which the capacity is 5 cube meters LNG per day, the numerical simulation and optimization for the LNG5 are carried out. It provides the composition of the mixed refrigerant. It analyzes the effects of mixed refrigerant components on the temperature difference of the heat exchangers and the vapor fraction of the key nodes. The analysis results show that a reasonable mixture ratio of mixed refrigerant is given, such as CH4 mole fraction being 41.8% ～ 44.3%, C2H6 mole fraction being 40.8% ～ 42.2%, C5H12 molar fraction being 14.3% ～ 16%, and N2 mole fraction being 1.5% ～ 3.3%. The results provide guidelines for the design of the small-scale CBM liquefaction device, and for the application and commissioning of CBM liquefaction plant in China.

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