Abstract: Natural deep eutectic solvents (NADES) show great promise as media for enzymatic reactions in areas where (bio)compatibility with natural or medicinal products is a must. While in theory they can be tailored to the intended reaction to ensure optimized yields, the knowledge to date is predominantly empirical, with some mechanistic reports providing a fragmented view at best. Therefore, it is not easy to explain experimental observations, let alone make predictions. The aim of this study was to develop a structured, holistic understanding of the effects of NADES media on enzymatic reactions, distinguishing between effects on solubility, solvation, viscosity, inhibition and denaturation. Experimental and computational chemistry methods were combined to separately study the interactions between enzyme, substrate, and NADES as reaction media. The initial enzyme activity and the final conversion of vinyl laurate transesterification by immobilized Candida antarctica lipase were studied experimentally. The direct effect of NADES on the same enzyme was modeled by molecular dynamics simulation. The effect of solubility was studied by both experimental and computational methods. To predict the solubility and viscosity of NADES, data-driven models were developed by combining group contribution and machine learning methods, based on the accumulated experimental knowledge on NADES found in the literature. Finally, the composed relationships and prediction models were applied to the practical example of deacetylation of mannosylerythritol lipids (MELs). The experimental findings show that the chosen NADES system has a significant effect on both the apparent initial activity and the final conversion. However, in the simulations, the enzyme retains its original structure; moreover, NADES has an additional stabilizing effect on the enzyme. In addition, changes in the molar ratio of the compounds in NADES do not show a significant effect on the stability of the enzyme. These results indicate that the main effect of NADES on the reaction is mainly related to the substrate-solvent interactions (solvation energy) and the viscosity of the system. On the other hand, the experimental results only confirmed the significance of solvation, viscosity did not show a clear correlation with the studied reaction parameters. The machine learning models built for solubility and viscosity gave quantitative predictions of these properties. The accumulated knowledge was used to optimize the yield in the deacetylation reaction of MELs. The combination of these methods provides fundamental knowledge about the effect of NADES on biocatalysis, but the results are also applicable to other uses of NADES.

Abstract: Identifying priority areas is an essential step in developing management strategies to reduce pesticide loads in surface water. A spatially explicit model-based approach was developed to detect priority areas for diffuse pesticide pollution at catchment scale. The method uses available datasets and considers different pesticide pathways in the environment post-application. The approach was applied in a catchment area in SE Flanders (Belgium) as a case study. Calculated risk areas were obtained using detailed landscape data and combining pesticide emissions and hydrological connectivity. The risk areas obtained were further compared with an alternative observation-based method, developed specifically for this study site that includes long-term field observations and local expert knowledge. Both methods equally classified 50% of the areas. The impact of crop rotation on the calculated risk was analysed. High-risk areas were identified and added to a cumulative map over all five years to evaluate temporal variations. The model-based approach was used for the initial identification of risk areas at the study site. The tool helps to prioritise zones and detect particular fields to target landscape mitigation measures to reduce diffuse pesticide pollution reaching surface water bodies.

Abstract: Increasingmass tourismcan generate importantmicroclimatic perturbations and also elevate indoor pollution by the transport of fine particulatematter. The purpose of this researchwas to study the indoor air conditions in the RoyalMuseum ofWawel Castle in Cracow, Poland, displaying amongst other valuable works of art also a unique collection of Flemish tapestries. The investigation involved in the determination of transport and deposition of particulate matter brought in by visitors. The microclimate inside the exhibition rooms was also monitored. Samples of suspended particulateswere collected inside and outside themuseuminwinterand summer2006.On days with intensive tourist visits the concentration of total suspended particulates was significantly higher (i.e., 130 µg/m3 inwinter and 49 µg/m3 in summer) than on those days without tourists (i.e., 73 µg/m3 and 22 µg/m3 in winter and summer, respectively). The concentrations of all investigated elementswere also considerably higher during the tourist flow. This was especially valid for soil dust associated elements (Si, K, Ca, Al, and Ti), with considerably higher levels in summer than winter. This could be linked with much more frequent tourist activity in the summer period. Also, the concentration of Clwasmuch higher inwinter than summer, due to the use of deicing salts on the roads and pavements.

Abstract: Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot directly be adapted to Gielis curves. Indeed, the different nature of their parameters forbids the use of a unified gradient descent approach, which requires initial pre-processings, such as the symmetry detection, and a reliable pose and scale estimation. Furthermore, even the most recent algorithms in the literature remain extremely sensitive to initialization and often fall into local minima in the presence of large missing data. We present a simple evolutionary algorithm which overcomes most of these issues and unifies all of the required operations into a single though efficient approach. The key ideas in this paper are the replacement of the potential fields used for the cost function (closed form) by the shortest Euclidean distance (SED, iterative approach), the construction of cost functions which minimize the shortest distance as well as the curve length using R-functions, and slight modifications of the evolutionary operators. We show that the proposed cost function based on SED and R-function offers the best compromise in terms of accuracy, robustness to noise, and missing data.

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.

Abstract: Starting from logarithmic, sinusoidal and power spirals, it is shown how these spirals are connected directly with Chebyshev polynomials, Lamé curves, with allometry and Antonelli-metrics in Finsler geometry. Curvature is a crucial concept in geometry both for closed curves and equiangular spirals, and allowed Dillen to give a general definition of spirals. Many natural shapes can be described as a combination of one of two basic shapes in nature—circle and spiral—with Gielis transformations. Using this idea, shape description itself is used to develop a novel approach to anisotropic curvature in nature. Various examples are discussed, including fusion in flowers and its connection to the recently described pseudo-Chebyshev functions.

Abstract: We generalize the Gielis Superformula by extending the R. Chacon approach, but avoiding the use of Jacobi elliptic functions. The obtained results are extended to the three-dimensional case. Several new shapes are derived by using the computer algebra system Mathematica(C).

Abstract: Determination of count losses and pile-up pulse effects in quantitative and qualitative analysis became a vital step in various analyses. Therefore, compensating for counting losses is of importance. These counting losses are due to the pulse pile-up, paralyzable and non-paralyzable system dead time or a combination of these mechanisms. In this work, a new method is suggested for the correction of dead time losses resulting from the above mechanisms. For this purpose, a source code was developed. It was found that the peaking time was an important parameter over system dead time. The method suggested seems to be more effective even at high count rate. (C) 2009 Elsevier B.V. All rights reserved.

Abstract: EU strategies for waste management have long recognized the key role of recycling to move towards sustainable consumption and production. This resulted in a range of regulatory measures, among which the Waste Electrical and Electronic Equipment (WEEE) directive, which sets weight-based targets for recovery, preparation for re-use and recycling. The increasing strategic relevance of the supply of raw materials has, however, spurred a more integrated approach towards resource efficiency. In addition to the prevention of disposal, recycling practices are now also meant to contribute to sustainable materials management by pursuing (i) a higher degree of material cycle closure, (ii) an improved recovery of strategically relevant materials, and (iii) the avoidance of environmental burdens associated with the extraction and refining of primary raw materials. In response to this evolution, this paper reports about the development of an indicator set that allows to quantitatively demonstrate these recycling benefits, hence going further than the weight-based objectives employed in the WEEE directive. The indicators can be calculated for WEEE recycling processes for which information is available on both input and output fractions. It offers a comprehensive framework that aims to support decision making processes on product design, to identify opportunities for the optimization of WEEE End-of-Life scenarios, and to assess the achieved (or expected) results of implemented (or planned) recycling optimization strategies. The paper is illustrated by a case study on the recycling of LCD televisions. (C) 2014 Elsevier Ltd. All rights reserved.

Abstract: In this paper the possibilities and limitations of a non-invasive prototype of macroscopic X-ray powder diffraction scanning device employed in transmission and reflection mode are demonstrated. Contrarily to e.g. macroscopic X-ray fluorescence scanners, which gather information on the elemental level, the prototype instrument allows to obtain information on the crystallographic structure of the components. When applied to cultural heritage artefacts, it becomes possible to identify and localize crystalline pigments. Furthermore, it became clear that different information can be available depending on the geometry of the scanner components. In transmission mode information over the entire stratigraphy of the painting is gathered, which is useful to e.g. identify background substrates and major pigments. On the other hand, reflection-XRPD is a surface-sensitive technique and allows the identification of pigments and degradation products located on the surface. The data acquired during both experiments can be presented as two-dimensional distribution maps which show the spatial distribution of every identified pigment. The complementary nature of transmission and reflectionmode makes it possible to gain more insight into the stratigraphy of the painting which is valuable information for conservation and restoration scientists.

Abstract: Through a combined use of light- and electron microscopy with microanalytical techniques, the aluminium distribution in gills of aluminium-exposed catfish was investigated. This study demonstrates that also with the ''acid-resistant'' catfish, exposed during seven days to acidified water (pH=4.3) with an elevated aluminium concentration (1 mg Al/l), aluminium can be found at, and even in, the gills.