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M Giorgini

Publications and source records attributed to M Giorgini.

4 recordsLinked to original sources

Molecular characterization of closely related species in the parasitic genus Encarsia (Hymenoptera: Aphelinidae) based on the mitochondrial cytochrome oxidase subunit I gene.

The genus Encarsia Förster includes parasitoid species that are effective natural enemies of whitefly and armoured scale insect agricultural pests. Within this genus, several species groups have been recognized on the basis of morphological similarity, although their monophyly appears uncertain. It is often difficult to separate morphologically similar species, and there is evidence that some species could in fact be complexes of cryptic species. Their correct identification is fundamental for biological control purposes. Recently, due to unreliability of morphological characters, molecular techniques have been investigated to identify markers that differentiate closely related species. In this study, DNA variation in an approximately 900 bp segment of the mitochondrial cytochrome oxidase subunit I (COI) gene was examined by both sequencing and PCR-RFLP. Two pairs of species that are difficult to distinguish morphologically were analysed: Encarsia formosa Gahan and Encarsialuteola Howard, belonging to the luteola group, and two populations of Encarsiasophia (Girault & Dodd) from Pakistan and Spain, belonging to the strenua group, recently characterized as cryptic species. High sequence divergence and species-specific restriction patterns clearly differentiate both species pairs. Parsimony analysis of the nucleotide sequences was also performed, including Encarsiahispida De Santis (luteola group) and Encarsia protransvena Viggiani (strenua group). Two monophyletic clades supporting the two groups of species considered were resolved. The results of this study support the use of the COI gene as a useful marker in separating species of Encarsia, for which morphological differences are subtle. Moreover, the COI gene appears potentially useful for understanding phylogenetic relationships in this genus.

Animals↗

Selective Influence and Response Time Cumulative Distribution Functions in Serial-Parallel Task Networks.

We analyze sets of mental processes, some of which are concurrent and some of which are sequential, under the assumption that the processes are partially ordered, that is, arranged in a directed acyclic network. Information about the process arrangement can be discovered by examining the effects on response time of selectively influencing process durations. Previous work has mainly focused on analyses of mean response times. Here we consider analyses based on cumulative distribution functions, for one of the major classes of directed acyclic networks, serial-parallel networks. When two processes are selectively influenced, patterns in the cumulative distribution functions can be used to test whether the processes are sequential or concurrent and whether the task network has AND gates or OR gates. Cumulative distribution functions are potentially more informative than means, and some previous results for means are shown to follow from our results for cumulative distribution functions. Copyright 2000 Academic Press.

Journal Article↗

Response time distributions: some simple effects of factors selectively influencing mental processes.

When hypotheses about mental processing are tested with response times, inferences are often based on means, and occasionally on variance or skewness. Calculations on entire distributions of response times are more informative and can be conveniently carried out. Recently investigators have been updating procedures primarily based on means (such as additive factors tests) to procedures employing entire distribution functions. In one such advance, Nozawa and Townsend upgraded earlier tests of whether factors selectively influence serial or parallel processes, and whether parallel processes enter AND gates or OR gates. We discuss generalizations of the tests to complex arrangements of processes in networks. Results for a particularly difficult network, the Wheatstone bridge, are presented here. We use simulations to demonstrate the feasibility of the tests, and the possibility of mimicking.

Humans↗