Abstract: The development of advanced methods for non-destructive selective imaging of painted works of art at the macroscopic level based on radiation in the X-ray and infrared range of the electromagnetic spectrum are concisely reviewed. Such methods allow to either record depth-selective, element-selective or species-selective images of entire paintings. Camera-based full field methods (that record the image data in parallel) can be discerned next to scanning methods (that build up distributions in a sequential manner by scanning a beam of radiation over the surface of an artefact). Six methods are discussed: on the one hand, macroscopic X-ray fluorescence and X-ray diffraction imaging and X-ray laminography and on the other hand macroscopic Mid and Near Infrared hyper- and full spectral imaging and Optical Coherence Tomography. These methods can be considered to be improved versions of the well-established imaging methods employed worldwide for examination of paintings, i.e., X-ray radiography and Infrared reflectography. Possibilities and limitations of these new imaging techniques are outlined.

Abstract: Part of the collection of the Rubens House in Antwerp is a portrait of young Anthony van Dyck, alternatively attributed to Peter Paul Rubens and his pupil Anthony van Dyck. In order to reconstruct the genesis of the portrait in a manner that improves upon past investigations, a number of high-end technological methods, such as X-radiography, X-ray computer tomography, mammographic tomosynthesis and macroscopic X-ray fluorescence, have been employed to render the overpainted layers visible again. The results of the interdisciplinary examinations of the portrait of the youthful Van Dyck are impressive. The combined results allow the later additions to be peeled away until the original composition can be reached. Several pentimenti are easily discernible and refer to a rather immature hand that makes the authorship of Peter Paul Rubens very unlikely. What emerges is a portrait of an ambitious young man with a luxuriant head of hair and a slightly turned-up collar. The hat and cape were added later. The facial features are more recognisable and the execution of the bold curls points irrefutably in the direction of Anthony van Dyck as the author of his own portrait.

Abstract: The selection and identification of a suitable hydrological model structure is a more challenging task than fitting parameters of a fixed model structure to reproduce a measured hydrograph. The suitable model structure is highly dependent on various criteria, i.e. the modeling objective, the characteristics and the scale of the system under investigation and the available data. Flexible environments for model building are available, but need to be assisted by proper diagnostic tools for model structure selection. This paper introduces a qualitative method for model component sensitivity analysis. Traditionally, model sensitivity is evaluated for model parameters. In this paper, the concept is translated into an evaluation of model structure sensitivity. Similarly to the one-factor-at-a-time (OAT) methods for parameter sensitivity, this method varies the model structure components one at a time and evaluates the change in sensitivity towards the output variables. As such, the effect of model component variations can be evaluated towards different objective functions or output variables. The methodology is presented for a simple lumped hydrological model environment, introducing different possible model building variations. By comparing the effect of changes in model structure for different model objectives, model selection can be better evaluated. Based on the presented component sensitivity analysis of a case study, some suggestions with regard to model selection are formulated for the system under study: (1) a non-linear storage component is recommended, since it ensures more sensitive (identifiable) parameters for this component and less parameter interaction; (2) interflow is mainly important for the low flow criteria; (3) excess infiltration process is most influencing when focussing on the lower flows; (4) a more simple routing component is advisable; and (5) baseflow parameters have in general low sensitivity values, except for the low flow criteria. (C) 2014 Elsevier B.V. All rights reserved.