Browsing by Subject "Sampling"

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    On howtrap positioning affects phlebotomine sand fly density estimations
    (Wiley, 2021-09) Muñoz, C.; Pérez Cutillas, P.; Berriatua, E.; Ortiz Sánchez, Juana; Sanidad Animal
    There is a need for standardizing sand fly sampling methodology and guidance on trap positioning for quantitative sand fly studies. We investigated differences in sand fly density with ‘sticky’ interception and CO2-light attraction traps, in relation to trap distance to the ground and the presence or absence of a continuous or discontinuous (wire mesh) vertical surface adjacent to the trap. The study, conducted in a dog kennel in southeast Spain, lasted 48 days and collected 692 Phlebotomus papatasi, P. perniciosus, P. ariasi and Sergentomyia minuta specimens. There were no significant differences between species with respect to trap position. Overall, density in sticky traps was highest closest to the ground and next to the continuous vertical surface, followed sequentially by traps similarly placed adjacent to the wire mesh and those hanging from a rope across the kennel yard. In contrast, density in CO2-light traps was highest in traps hanging from the rope near the ground, followed by those next to the continuous vertical surface. The overall negative relationship between sand fly density and ground distance was not significant for CO2-light traps next to the continuous vertical surface. Modelling also suggested that sand flies do not use the wire mesh to move vertically.
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    Selección de una muestra de títulos propios de la Universidad de Sevilla para su posterior evaluación
    (2003-07-01) López Romero, Mª Angeles
    This paper describes how a sample of postgraduate programs offered at the University of Seville during the biennium 1999-2001 was selected in order to conduct a rear in-depth evaluation. The first section examines the data collection procedures, based on the review of some characteristics that define with precision the whole of the programs offered. The statistics techniques used to analyse data, basically correlational techniques (Multiple Correspondence Analysis), based on the association among variables, are also described. Finally, the main findings are provided, including the resulting sample, made up of six programs.