Experimental simulation of ancient hybridization between bank and red voles

2008 ◽  
Vol 420 (1) ◽  
pp. 169-171 ◽  
Author(s):  
O. V. Osipova ◽  
A. A. Soktin
Keyword(s):  
Experimental Simulation ◽  
Ancient Hybridization

Diversification of the North American Doellingeria-Eucephalus Clade (Astereae: Asteraceae) Inferred from Molecular and Morphological Evidence

2019 ◽  
Vol 44 (4) ◽  
pp. 930-942
Author(s):  
Geraldine A. Allen ◽  
Luc Brouillet ◽  
John C. Semple ◽  
Heidi J. Guest ◽  
Robert Underhill
Keyword(s):  
North American ◽  
Sequence Data ◽  
Phylogenetic Analyses ◽  
Sister Group ◽  
Morphological Evidence ◽  
South American ◽  
New Combinations ◽  
The North ◽  
Hybridization Event ◽  
Ancient Hybridization

Abstract—Doellingeria and Eucephalus form the earliest-diverging clade of the North American Astereae lineage. Phylogenetic analyses of both nuclear and plastid sequence data show that the Doellingeria-Eucephalus clade consists of two main subclades that differ from current circumscriptions of the two genera. Doellingeria is the sister group to E. elegans, and the Doellingeria + E. elegans subclade in turn is sister to the subclade containing all remaining species of Eucephalus. In the plastid phylogeny, the two subclades are deeply divergent, a pattern that is consistent with an ancient hybridization event involving ancestral species of the Doellingeria-Eucephalus clade and an ancestral taxon of a related North American or South American group. Divergence of the two Doellingeria-Eucephalus subclades may have occurred in association with northward migration from South American ancestors. We combine these two genera under the older of the two names, Doellingeria, and propose 12 new combinations (10 species and two varieties) for all species of Eucephalus.

Erratum: Experimental simulation of the closed deivertor system for nuclear fusion, (Vol.23, 3^|^4, pp.22-25)

2012 ◽  
Vol 23 (3+4) ◽  
pp. E1-E1
Author(s):  
Suguru TANAKA ◽  
Hiroyasu KOMUKAI ◽  
Akira TONEGAWA ◽  
Kazutaka KAWAMURA
Keyword(s):  
Nuclear Fusion ◽  
Experimental Simulation

scholarly journals Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

2009 ◽  
Vol 132 (3) ◽  
Author(s):  
Donald L. Simon ◽  
Sanjay Garg
Keyword(s):  
Kalman Filter ◽  
Estimation Error ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Performance Estimation ◽  
Experimental Simulation ◽  
Tuning Parameter ◽  
Estimation Accuracy ◽  
On Line

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multivariable iterative search routine that seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared with the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy.

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