Abstract: The combination of several micro-XRF analysis modes is presented for the investigation of an illuminated parchment manuscript. With a commercial instrument, conventional micro-XRF spot analysis (0D) and mapping (2D) are performed, yielding detailed lateral elemental information. Depth resolution becomes accessible by mounting an additional polycapillary lens in front of an SDD detector. Quantitative confocal depth profiles (1D) are presented as well as the full separation of the front and the backside decorations with the help of fast 3D mappings of specific areas. Only through the use of these multidimensional modes can elemental information be assigned both to lateral and depth positions, making the analysis of such heterogeneous samples feasible.

Abstract: We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods.

Abstract: The molecular genetics of flower development have been studied extensively for more than two decades. Fusion of organs and the tendency to oligomery, important characteristics of flower evolution, so far have remained fairly elusive. We present a geometric model for shape and fusion in the corolla of Asclepiads. Examples demonstrate how fusion of petals creates stable centers, a prerequisite for the formation of complex pollination structures via congenital and postgenital fusion events, with the formation of de novo organs, specific to Asclepiads. The development of the corolla reduces to simple inequalities from the MATHS-BOX. The formation of stable centers and of bell and tubular shapes in flowers are immediate and logical consequences of the shape. Our model shows that any study on flowers, especially in evo-devo perspective should be performed within the wider framework of polymery and oligomery and of fusion and synorganization.

Abstract: Diatoms represent the major component of phytoplankton and are responsible for about 2025% of global primary production. Hundreds of millions of years of evolution led to tens of thousands of species differing in dimensions and morphologies. In particular, diatom porous silica cell walls, the frustules, are characterized by an extraordinary, species-specific diversity. It is of great interest, among the marine biologists and geneticists community, to shed light on the origin and evolutionary advantage of this variability of dimensions, geometries and pore distributions. In the present article the main reported data related to frustule morphogenesis and functionalities with contributions from fundamental biology, genetics, mathematics, geometry and physics are reviewed.

Abstract: Several HNO3-based leaching approaches were tested and optimized to selectively recover Pb and other minor metals (Cu, Ni, Zn) from secondary lead smelter residues (i.e., slag and matte). Firstly, the leaching behaviors of Pb and the matrix element Fe were studied at atmospheric pressure in the temperature range 25-70 degrees C. These elements were present in both materials studied as sulfide and oxide phases. For the sulfur-rich matte residue, the Pb leaching increased from 63% to 69% upon increasing the HNO3 concentration from 0.2 M to 0.5 M. However, by adding Fe(III) as an oxidation agent, Pb leaching from the matte amounted to 90% at 25 degrees C. At a higher temperature, Pb leaching was reduced due to PbSO4 precipitation. In this process, Cu, Zn and Ni leaching was insignificant. For the slag residue, HNO3 could not leach Pb (0.03% Pb leached), while Fe leaching was 19.8% due to a galvanic effect. However, Pb leaching of the slag was 82% in the presence of additional Fe(III). Secondly, to enhance leaching of the other base metals (Cu, Zn and Ni) from the matte, roasting followed by water leaching and (microwave assisted or autoclave) pressurized leaching in 0.5 M HNO3 were applied. During roasting, the FeS phase converted to Fe2O3 above 500 degrees C, and PbS and Pb phases were transformed into insoluble PbSO4 above 400 degrees C. Cu, Ni and Zn leaching was drastically enhanced by a roasting step at 600 degrees C followed by leaching with 0.5 M HNO3 at 50 degrees C, or by pressurized HNO3 leaching above 130 degrees C, whereby Pb leaching almost ceased due to PbSO4 precipitation. During the roasting above 600 degrees C, or microwave assisted extraction (MAE) at 160 degrees C for 15 min, FeS was completely converted to iron oxides that can be used as raw material for pig iron production. Based on the results, the methods investigated can be combined as process steps of two possible routes for the selective recovery of valuable metals and the production of a clean source of Fe oxides from the secondary lead smelting residues studied. (C) 2017 Elsevier B.V. All rights reserved.

Abstract: A quasi 3D modelling approach was developed by integrating a crop growth (LINGRA-N) and a hydrological model (Hydrus-1D) to simulate and visualize water flow, soil-water storage, water stress and crop yield over a heterogeneous sandy field. We assessed computational efficiency and uncertainty with low to high-spatial resolution input factors (soil-hydraulic properties, soil-layer thickness and groundwater level) and evaluated four irrigation scenarios (no, current, optimized and triggered) to find the optimal and cost-effective irrigation scheduling. Numerical results showed that the simulation uncertainty was reduced when using the high-resolution information while a fast performance was maintained. The approach accurately determined the field scale irrigation requirements, taking into account spatial variations of input information. Optimal irrigation scheduling is obtained by triggered-irrigation resulting in saving up to similar to 300% water as compared to the current-irrigation, while yield increased similar to 1%. Overall, the approach can be useful to help decision makers and applicants in precision farming. (C) 2017 Published by Elsevier Ltd.

Abstract: The ability of urban wastewater systems to adapt and transform as a response to change is an integral part of sustainable development. This requires technology and infrastructure that can be adapted to new operational challenges. In this study the adaptive capacity of urban wastewater systems is evaluated by assessing the interdependencies between system components. In interdependent and therefore tightly coupled systems, changes to one systems component will require alteration elsewhere in the system, therefore impairing the capacity of these systems to be changed. The aim of this paper is to develop a methodology to evaluate the adaptive capacity of urban wastewater systems by assessing how change drivers and innovation affect existing wastewater technology and infrastructure. The methodology comprises 7 steps and applies a change impact table and a design structure matrix that are completed by experts during workshops. Change impact tables quantify where change drivers, such as energy neutrality and resource recovery, require innovation in a system. The design structure matrix is a tool to quantify emerging changes that are a result of the innovation. The method is applied for the change driver of energy neutrality and shown for two innovations: a decentralised upflow anaerobic sludge blanket reactor followed by an anammox process and a conventional activated sludge treatment with enhanced chemical precipitation and high temperature-high pressure hydrolysis. The results show that the energy neutrality of wastewater systems can be address by either innovation in the decentralised or centralised treatment. The quantification of the emerging changes for both innovations indicates that the decentralised treatment is more disruptive, or in other words, the system needs to undergo more adaptation. It is concluded that the change impact and change propagation method can be used to characterise and quantify the technological or infrastructural transformations. In addition, it provides insight into the stakeholders affected by change.

Abstract: Sustainable wastewater treatment has been attracting increasing attentions over the past decades. However, the production of nitrous oxide (N2O), a potent GHG, from the energy-efficient granule-based autotrophic nitrogen removal is largely unknown. This study applied a previously established N2O model, which incorporated two N2O production pathways by ammonia-oxidizing bacteria (AOB) (AOB denitrification and the hydroxylamine (NH2OH) oxidation). The two-pathway model was used to describe N2O production from a granule-based partial nitritation (PN) reactor and provide insights into the N2O distribution inside granules. The model was evaluated by comparing simulation results with N2O monitoring profiles as well as isotopic measurement data from the PN reactor. The model demonstrated its good predictive ability against N2O dynamics and provided useful information about the shift of N2O production pathways inside granules for the first time. The simulation results indicated that the increase of oxygen concentration and granule size would significantly enhance N2O production. The results further revealed a linear relationship between N2O production and ammonia oxidation rate (AOR) (R-2 = 0.99) under the conditions of varying oxygen levels and granule diameters, suggesting that bulk oxygen and granule size may exert an indirect effect on N2O production by causing a change in AOR.