Tree resolution and generalized semantic tree

Author(s):  
S Kundu
2012 ◽  
Vol 10 (1) ◽  
pp. 19-44 ◽  
Author(s):  
Alfy Morales-Cazan ◽  
James S. Albert

The systematics and taxonomy of poeciliid fishes (guppies and allies) remain poorly understood despite the relative importance of these species as model systems in the biological sciences. This study focuses on testing the monophyly of the nominal poeciliine tribe Heterandriini and the genus Heterandria, through examination of the morphological characters on which the current classification is based. These characters include aspects of body shape (morphometrics), scale and fin-ray counts (meristics), pigmentation, the cephalic laterosensory system, and osteological features of the neurocranium, oral jaws and suspensorium, branchial basket, pectoral girdle, and the gonopodium and its supports. A Maximum Parsimony analysis was conducted of 150 characters coded for 56 poeciliid and outgroup species, including 22 of 45 heterandriin species (from the accounted in Parenti & Rauchenberger, 1989), or seven of nine heterandriin species (from the accounted in Lucinda & Reis, 2005). Multistate characters were analyzed as both unordered and ordered, and iterative a posteriori weighting was used to improve tree resolution. Tree topologies obtained from these analyses support the monophyly of the Middle American species of "Heterandria," which based on available phylogenetic information, are herein reassigned to the genus Pseudoxiphophorus. None of the characters used in previous studies to characterize the nominal taxon Heterandriini are found to be unambiguously diagnostic. Some of these characters are shared with species in other poeciliid tribes, and others are reversed within the Heterandriini. These results support the hypothesis that Pseudoxiphophorus is monophyletic, and that this clade is not the closest relative of H. formosa (the type species) from southeastern North America. Available morphological data are not sufficient to assess the phylogenetic relationships of H. formosa with respect to other members of the Heterandriini. The results further suggest that most tribe-level taxa of the Poeciliinae are not monophyletic, and that further work remains to resolve the evolutionary relationships of this group.


2017 ◽  
Vol 30 (3) ◽  
pp. 503-525
Author(s):  
Kamal Hamaz ◽  
Fouzia Benchikha

Purpose With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as the most used model for data storage and manipulation. However, it does not offer any semantic support for the stored data which can facilitate data access for the users. Indeed, a large number of users are intimidated when retrieving data because they are non-technical or have little technical knowledge. To overcome this problem, researchers are continuously developing new techniques for Natural Language Interfaces to Databases (NLIDB). Nowadays, the usage of existing NLIDBs is not widespread due to their deficiencies in understanding natural language (NL) queries. In this sense, the purpose of this paper is to propose a novel method for an intelligent understanding of NL queries using semantically enriched database sources. Design/methodology/approach First a reverse engineering process is applied to extract relational database hidden semantics. In the second step, the extracted semantics are enriched further using a domain ontology. After this, all semantics are stored in the same relational database. The phase of processing NL queries uses the stored semantics to generate a semantic tree. Findings The evaluation part of the work shows the advantages of using a semantically enriched database source to understand NL queries. Additionally, enriching a relational database has given more flexibility to understand contextual and synonymous words that may be used in a NL query. Originality/value Existing NLIDBs are not yet a standard option for interfacing a relational database due to their lack for understanding NL queries. Indeed, the techniques used in the literature have their limits. This paper handles those limits by identifying the NL elements by their semantic nature in order to generate a semantic tree. This last is a key solution towards an intelligent understanding of NL queries to relational databases.


Plant Biology ◽  
2012 ◽  
Vol 15 (5) ◽  
pp. 858-867 ◽  
Author(s):  
G. D. S. Seger ◽  
L. D. S. Duarte ◽  
V. J. Debastiani ◽  
A. Kindel ◽  
J. A. Jarenkow

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