
 Possibilities for compositional tailoring of Norway spruce (Picea abies
 L. Karst.) wood using a hydrophobic oil impregnation process

ZusammenfassungImpregnation with hydrophobic oils offers non-toxic options for preserving Norway spruce (Picea abies L. Karst) wood that could potentially be used to tailor the properties
 of wood products, especially those used in exposed conditions. The objective of this study was to quantify
 the effects of the water-filled porosity and density of Norway spruce wood and treatments (applied to set
 the wood’s water contents at desired test levels) prior to impregnation with the linseed oil derivative
 Linogard by the Linotech process on its oil retention. Retention of oil differed significantly between
 tissue types. Dried specimens always retained less oil than corresponding undried or rewetted specimens.
 Furthermore, water-filled porosity and density had significant effects on oil retention levels within tissue
 types, allowing linear regression equations to be developed that gave good predictions of oil retention
 parameters for different tissues, with R2 values ranging from 0.66 for mature
 heartwood to 0.85 for mature sapwood. Thus there is scope to use hydrophobic oil impregnation processes
 for producing compositionally tailored wood materials with specified properties.

Near-infrared spectroscopy for the quantification of linseed oil uptake in Scots pine (Pinus sylvestris L.)
Abstract Eighteen sapwood and 18 heartwood samples from three Scots pine (Pinus sylvestris L.) trees were used to identify correlations between the features of their near-infrared spectra (400–2500 nm) measured before and after impregnation with linseed oil (Linogard®) and (1) the amount of oil taken up by the samples at three different longitudinal positions; and (2) the tissue type of sample. Calibration models were cross-validated and oil uptake models were also validated on separate test sets. Partial least squares regression models for the prediction of uptake and tissue type in non-impregnated wood were promisingly accurate, having coefficients of multiple determination (Q 2) values of > 0.8, 0.8 and 0.75 for predictions of tissue type, oil taken up as a percentage of sample mass and total mass of oil taken up, respectively. The models developed for linseed oil-impregnated samples were better still, generating Q 2 values of > 0.9, > 0.8 and 0.8 for the three key properties. In general, models based on spectra acquired along two directions of measurement (longitudinal and tangential) were more accurate than models based on only one. Tandem models consisting of two submodels, one for sapwood and one for heartwood, were more successful than single models applicable to both tissue types.
The Three Faces of Defeasibility in the Law
In this paper we will analyse the issue of defeasibility in the law, taking into account research carried out in philosophy, artificial intelligence and legal theory. We will adopt a very general idea of legal defeasibility, in which we will include all different ways in which certain legal conclusions may need to be abandoned, though no mistake was made in deriving them. We will argue that defeasibility in the law involves three different aspects, which we will call inference-based defeasibility, process-based defeasibility, and theory-based defeasibility. Only the integration of these three perspectives allows us to provide a satisfactory account of the role of defeasibility in legal reasoning.