Seedling Characters and Phylogenetic Relationships in the Informal Series Ovatae of Eucalyptus, Subgenus Symphyomyrtus

1984 ◽  
Vol 32 (1) ◽  
pp. 1 ◽  
Author(s):  
PY Ladiges ◽  
MB Dale ◽  
DR Ross ◽  
KG Shields

Using seedling characters, the relationships of 16 taxa of the informal series Ovatae of Eucaiyptus were investigated. The method of multidimensional unfolding proved useful in determining ancestral states of different characters and testing for conformity amongst characters when outgroup comparison was not possible. The analyses included Wagner trees, a branch and bound algorithm (which produced the shortest trees) and an additive similarity tree. Neighbour relationships were examined using a network procedure (TWONET). The results suggested that series Ovatae is a paraphyletic group, although one subgroup, approximately equivalent to subseries Ovatinae, is probably monophyletic. The biogeography and ecology of the taxa support this conclusion. A broader study of section Maidenaria is recommended before taxonomic revision.

Author(s):  
Bishaljit Paul ◽  
Sushovan Goswami ◽  
Dipu Mistry ◽  
Chandan Kumar Chanda

Author(s):  
Jan-Lucas Gade ◽  
Carl-Johan Thore ◽  
Jonas Stålhand

AbstractIn this study, we consider identification of parameters in a non-linear continuum-mechanical model of arteries by fitting the models response to clinical data. The fitting of the model is formulated as a constrained non-linear, non-convex least-squares minimization problem. The model parameters are directly related to the underlying physiology of arteries, and correctly identified they can be of great clinical value. The non-convexity of the minimization problem implies that incorrect parameter values, corresponding to local minima or stationary points may be found, however. Therefore, we investigate the feasibility of using a branch-and-bound algorithm to identify the parameters to global optimality. The algorithm is tested on three clinical data sets, in each case using four increasingly larger regions around a candidate global solution in the parameter space. In all cases, the candidate global solution is found already in the initialization phase when solving the original non-convex minimization problem from multiple starting points, and the remaining time is spent on increasing the lower bound on the optimal value. Although the branch-and-bound algorithm is parallelized, the overall procedure is in general very time-consuming.


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