La inmaterialidad de las sustancias espirituales (Santo Tomás versus Avicebrón)

El presente trabajo de investigación sobre el pensamiento de Santo Tomás acerca de la inmaterialidad de las sustancias espirituales se centra en la I q. 50 a. 2 de la Summa Theologiae. El artículo escogido se ubica casi al comienzo del tratado tomista sobre la creación y plantea en toda su crudeza la validez o no de ese sobrenombre que Chesterton ideó para Santo Tomás, Thomas a Creatore. En este pasaje se resume el punto central de la metafísica: ¿qué es lo que me distingue a mí radicalmente y a todos los seres existentes, de Dios? ¿qué somos propiamente? Santo Tomás responde: somos creaturas. Hay algo que marca profundamente al mundo que nos rodea y al hombre, y esto es —como señala Pieper— el ser creación, el tener la condición de ser algo creado. Y en qué consiste tal condición? En estar compuesto. ¿Pero de qué? De essentia y actus essendi, no necesariamente de materia y forma. Con tal afirmación el Aquinantense derrumba en un instante toda la tradición de ochocientos años, realimentada en plena Edad Media por el Fons vitae de Avicebrón

Aportación al estudio palinológico del género quercus en Galicia

Se realiza el estudio biométrico del polen de Quercus r obur L., Q_ petraea Liebl., Q. pyrenaica Will., Q. i l ex L. y Q. s uber L., de muestras recogidas en disti nta·s localidades gal l egas , obteniendose la dimensión y relación dimensional más significativa para su diferenciación . Se aplican estos resul tactos al análi,sis pol inice de la laguna colmatada de La Lucenza (Lugo}, donde existe un espectro continuo de Quercus , e n l a que se observa un aumento progresivo del tamaño de grano de polen con la profundidad.on réalise une étude biométrique du pollen de Quercus robur L. , Q. petraea Liebl., Q. pyr enaica Will., Q. i l ex L., Q_ s uber L. La taille et l e rapport des dimens i ons le plus significatif pour leur diffé r entiation sont presenté es . Les résul tats sont apliquées a 1' anal yse pollinique d 'une lacune encombrée (La Lucenza, Lugo) , ou on peut apprecér un spectre conti nu du genre Quercus , ayant l ieu une augmentation progre si ve de la taille des gra ins de pol l en avec la prof undeur

Spatial Models for Field Trials

An important aim of the analysis of agricultural field trials is to obtain good predictions for genotypic performance, by correcting for spatial effects. In practice these corrections turn out to be complicated, since there can be different types of spatial effects; those due to management interventions applied to the field plots and those due to various kinds of erratic spatial trends. This paper presents models for field trials in which the random spatial component consists of tensor product Penalized splines (P-splines). A special ANOVA-type reformulation leads to five smooth additive spatial components, which form the basis of a mixed model with five unknown variance components. On top of this spatial field, effects of genotypes, blocks, replicates, and/or other sources of spatial variation are described by a mixed model in a standard way. We show the relation between several definitions of heritability and the effective dimension or the effective degrees of freedom associated to the genetic component. The approach is illustrated with large-scale field trial experiments. An R-package is provided

Correcting for spatial heterogeneity in plant breeding experiments with P-splines

An important aim of the analysis of agricultural field experiments is to obtain good predictions for genotypic performance, by correcting for spatial effects. In practice these corrections turn out to be complicated, since there can be different types of spatial effects; those due to management interventions applied to the field plots and those due to various kinds of erratic spatial trends. This paper explores the use of two-dimensional smooth surfaces to model random spatial variation. We propose the use of anisotropic tensor product P-splines to explicitly model large-scale (global trend) and small-scale (local trend) spatial dependence. On top of this spatial field, effects of genotypes, blocks, replicates, and/or other sources of spatial variation are described by a mixed model in a standard way. Each component in the model is shown to have an effective dimension. They are closely related to variance estimation, and helpful for characterising the importance of model components. An important result of this paper is the formal proof of the relation between several definitions of heritability and the effective dimension associated with the genetic component. The practical value of our approach is illustrated by simulations and analyses of large-scale plant breeding experiments. An \texttt{R}-package, \texttt{SpATS}, is provide