A Steady-state prediction of Dye 3 core features

1985 ◽  
pp. 111-117 ◽  
Author(s):  
B. McInnes ◽  
U. Radok
Keyword(s):  
Steady State ◽  
State Prediction ◽  
Core Features

Maximal Lactate Steady-State Prediction Through Quadratic Modeling of Selected Stages of the Lactate Minimum Test

2008 ◽  
Vol 22 (4) ◽  
pp. 1073-1080 ◽  
Author(s):  
Emerson Pardono ◽  
Rafael da Costa Sotero ◽  
Wolysson Hiyane ◽  
Marcio Rabelo Mota ◽  
Carmen Silvia Grubert Campbell ◽  
...  
Keyword(s):  
Steady State ◽  
Maximal Lactate Steady State ◽  
State Prediction ◽  
Lactate Minimum

Improvement in Control Performance of a Weigh Feeder Using Steady-state Prediction

2016 ◽  
Vol 136 (5) ◽  
pp. 728-729 ◽  
Author(s):  
Takao Sato ◽  
Yoshihiro Ohnishi ◽  
Toru Yamamoto ◽  
Yasuo Konishi
Keyword(s):  
Steady State ◽  
Control Performance ◽  
State Prediction

Maximal Lactate Steady-State Prediction

2010 ◽  
Vol 40 (2) ◽  
pp. 179-180 ◽  
Author(s):  
Tiago R. Figueira ◽  
Herbert G. Simões ◽  
Benedito S. Denadai
Keyword(s):  
Steady State ◽  
Maximal Lactate Steady State ◽  
State Prediction

scholarly journals Moon meteoritic seismic hum: Steady state prediction

2009 ◽  
Vol 114 (E12) ◽  
Author(s):  
Philippe Lognonné ◽  
Mathieu Le Feuvre ◽  
Catherine L. Johnson ◽  
Renee C. Weber
Keyword(s):  
Steady State ◽  
State Prediction

scholarly journals Mechanism of optimal time-course COVID-19 vaccine prioritization based on non-Markovian steady-state prediction

2021 ◽  
Author(s):  
Mi Feng ◽  
Liang Tian ◽  
Changsong Zhou
Keyword(s):  
Steady State ◽  
Time Course ◽  
Age Groups ◽  
Epidemiological Data ◽  
Underlying Mechanism ◽  
High Risk Group ◽  
Optimal Time ◽  
Years Of Life Lost ◽  
State Prediction ◽  
Mutant Strains

Vaccination is essential for controlling the coronavirus disease (COVID-19) pandemic. An effective time-course strategy for the allocation of COVID-19 vaccines is crucial given that the global vaccine supply will still be limited in some countries/regions in the near future and that mutant strains have emerged and will continue to spread worldwide. Both asymptomatic and symptomatic transmission have played major roles in the COVID-19 pandemic, which can only be properly described as a typical non-Markovian process. However, the prioritization of vaccines in the non-Markovian framework still lacks sufficient research, and the underlying mechanism of the time-course vaccine allocation optimization has not yet been uncovered. In this paper, based on an age-stratified compartmental model calibrated through clinical and epidemiological data, we propose optimal vaccination strategies (OVS) through steady-state prediction in the non-Markovian framework. This OVS outperforms other empirical vaccine prioritization approaches in minimizing cumulative infections, cumulative deaths, or years of life lost caused by the pandemic. We found that there exists a fast decline in the prevention efficiency of vaccination if vaccines are solely administered to a selected age group, which indicates that the widely adopted strategy to continuously vaccinate high-risk group is not optimal. Through mathematical analysis of the model, we reveal that dynamic vaccine allocations to combinations of different age groups is necessary to achieve optimal vaccine prioritization. Our work not only provides meaningful references for vaccination in countries currently lacking vaccines and for vaccine allocation strategies to prevent mutant strains in the future, but also reveals the mechanism of dynamic vaccine allocation optimization, forming a theoretical and modelling framework empirically applicable to the optimal time-course prioritization.

Maximal Lactate Steady State Prediction Through Polynomial Modeling of the Three Stage Lactate Minimum Test

2006 ◽  
Vol 38 (Supplement) ◽  
pp. S505
Author(s):  
Emerson Pardono ◽  
Rafael da Costa Sotero ◽  
Wolysson Hiyane ◽  
Marcio Rabelo Mota ◽  
Carmen Silvia Grubert Campbell ◽  
...  
Keyword(s):  
Steady State ◽  
Maximal Lactate Steady State ◽  
State Prediction ◽  
Lactate Minimum ◽  
Polynomial Modeling
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