Abstract: The definition of Gielis curves allows for the representation of self intersecting curves. The analysis and the understanding of these representations is of major interest for the analytical representation of sectors bounded by multiple subsets of curves (or surfaces), as this occurs for instance in many natural objects. We present a construction scheme based on R-functions to build signed potential fields with guaranteed differential properties, such that their zero-set corresponds to the outer, the inner envelop, or combined subparts of the curve. Our framework is designed to allow for the definition of composed domains built upon Boolean operations between several distinct objects or some subpart of self-intersecting curves, but also provides a representation for soft blending techniques in which the traditional Boolean union and intersection become special cases of linear combinations between the objects' potential fields. Finally, by establishing a connection between R-functions and Lame curves, we can extend the domain of the p parameter within the R-p-function from the set of the even positive numbers to the real numbers strictly greater than 1, i.e. p is an element of]1, +infinity[.

Abstract: In this study, we applied cluster beam deposition (CBD) as a new approach for fabricating efficient plasmon-based photocatalytic materials. Au nanoclusters (AuNCs) produced in the gas phase were deposited on TiO2 P25-coated silicon wafers with coverage ranging from 2 to 8 atomic monolayer (ML) equivalents. Scanning Electron Microscopy (SEM) images of the AuNCs modified TiO2 P25 films show that the surface is uniformly covered by the AuNCs that remain isolated at low coverage (2 ML, 4 ML) and aggregate at higher coverage (8 ML). A clear relationship between AuNCs coverage and photocatalytic activity towards stearic acid photo-oxidation was measured, both under ultraviolet and green light illumination. TiO2 P25 covered with 4 ML AuNCs showed the best stearic acid photo-oxidation performance under green light illumination (Formal Quantum Efficiency 1.6 x 10-6 over a period of 93 h). These results demonstrate the large potential of gas-phase AuNCs beam deposition technology for the fabrication of visible light active plasmonic photocatalysts.

Abstract: To broaden the activity window of TiO2, a broadband plasmonic photocatalyst has been designed and optimized. This plasmonic ‘rainbow’ photocatalyst consists of TiO2 modified with gold–silver composite nanoparticles of various sizes and compositions, thus inducing a broadband interaction with polychromatic solar light. However, these nanoparticles are inherently unstable, especially due to the use of silver. Hence, in this study the application of the layer-by-layer technique is introduced to create a protective polymer shell around the metal cores with a very high degree of control. Various TiO2 species (pure anatase, PC500, and P25) were loaded with different plasmonic metal loadings (0–2 wt %) in order to identify the most solar active composite materials. The prepared plasmonic photocatalysts were tested towards stearic acid degradation under simulated sunlight. From all materials tested, P25 + 2 wt % of plasmonic ‘rainbow’ nanoparticles proved to be the most promising (56% more efficient compared to pristine P25) and was also identified as the most cost-effective. Further, 2 wt % of layer-by-layer-stabilized ‘rainbow’ nanoparticles were loaded on P25. These layer-by-layer-stabilized metals showed superior stability under a heated oxidative atmosphere, as well as in a salt solution. Finally, the activity of the composite was almost completely retained after 1 month of aging, while the nonstabilized equivalent lost 34% of its initial activity. This work shows for the first time the synergetic application of a plasmonic ‘rainbow’ concept and the layer-by-layer stabilization technique, resulting in a promising solar active, and long-term stable photocatalyst.

Abstract: Silver-polymer core–shell nanoparticles show interesting optical properties, making them widely applicable in the field of plasmonics. The uniformity, thickness and homogeneity of the polymer shell will affect the properties of the system which makes a thorough structural characterization of these core–shell silver-polymer nanoparticles of great importance. However, visualizing the shell and the particle simultaneously is far from straightforward due to the sensitivity of the polymer shell towards the electron beam. In this study, we use different 2D and 3D electron microscopy techniques to investigate different structural aspects of the polymer coating.

Abstract: Cluster beam deposition is employed for fabricating well-defined bimetallic plasmonic photocatalysts to enhance their activity while facilitating a more fundamental understanding of their properties. AuxAg1-x clusters with compositions (x = 0, 0.1, 0.3, 0.5, 0.7, 0.9 and 1) spanning the metals' miscibility range were produced in the gas-phase and soft-landed on TiO2 P25-coated silicon wafers with an optimal coverage of 4 atomic monolayer equivalents. Electron microscopy images show that at this coverage most clusters remain well dispersed whereas EXAFS data are in agreement with the finding that the deposited clusters have an average size of ca. 5 nm and feature the same composition as the ablated alloy targets. A composition-dependant electron transfer from Au to Ag that is likely to impart chemical stability to the bimetallic clusters and protect Ag atoms against oxidation is additionally evidenced by XPS and XANES. Under simulated solar light, AuxAg1-x clusters show a remarkable composition-dependent volcano-type enhancement of their photocatalytic activity towards degradation of stearic acid, a model compound for organic fouling on surfaces. The Formal Quantum Efficiency (FQE) is peaking at the Au0.3Ag0.7 composition with a value that is twice as high as that of the pristine TiO2 P25 under solar simulator. Under UV the FQE of all compositions remains similar to that of pristine TiO2. A classical electromagnetic simulation study confirms that among all compositions Au0.3Ag0.7 features the largest near-field enhancement in the wavelength range of maximal solar light intensity, as well as sufficient individual photon energy resulting in a better photocatalytic self-cleaning activity. This allows ascribing the mechanism for photocatalysis mostly to the plasmonic effect of the bimetallic clusters through direct electron injection and near-field enhancement from the resonant cluster towards the conduction band of TiO2. These results not only demonstrate the added value of using well-defined bimetallic nanocatalysts to enhance their photocatalytic activity but also highlights the potential of the cluster beam deposition to design tailored noble metal modified photocatalytic surfaces with controlled compositions and sizes without involving potentially hazardous chemical agents.

Abstract: The growing concern for the increase of the global warming effects due to anthropogenic activities raises the challenge of finding novel technological approaches to stabilize CO2 emissions in the atmosphere and counteract impinging interconnected issues such as desertification and loss of biodiversity. Biological-CO2 mitigation, triggered through biological fixation, is considered a promising and eco-sustainable method, mostly owing to its downstream benefits that can be exploited. Microorganisms such as cyanobacteria, green algae and some autotrophic bacteria could potentially fix CO2 more efficiently than higher plants, due to their faster growth. Some examples of the potential of biological-CO2 mitigation are reported and discussed in this paper. In arid and semiarid environments, soil carbon sequestration (CO2 fixation) by cyanobacteria and biological soil crusts is considered an eco-friendly and natural process to increase soil C content and a viable pathway to soil restoration after one disturbance event. Another way for biological-CO2 mitigation intensively studied in the last few years is related to the possibility to perform carbon dioxide sequestration using microalgae, obtaining at the same time bioproducts of industrial interest. Another possibility under study is the exploitation of specific chemotrophic bacteria, such as Ralstonia eutropha (or picketii) and related organisms, for CO2 fixation coupled with the production chemicals such as polyhydroxyalkanoates (PHAs). In spite of the potential of these processes, multiple factors still have to be optimized for maximum rate of CO2 fixation by these microorganisms. The optimization of culture conditions, including the optimal concentration of CO2 in the provided gas, the use of metabolic engineering and of dual purpose systems for the treatment of wastewater and production of biofuels and high value products within a biorefinery concept, the design of photobioreactors in the case of phototrophs are some of the issues that, among others, have to be addressed and tested for cost-effective CO2 sequestration.

Abstract: Regenerative life support systems (RLSS) will play a vital role in achieving self-sufficiency during long-distance space travel. Urine conversion into a liquid nitrate-based fertilizer is a key process in most RLSS. This study describes the effects of simulated microgravity (SMG) on Comamonas testosteroni, Nitrosomonas europaea, Nitrobacter winogradskyi and a tripartite culture of the three, in the context of nitrogen recovery for the Micro-Ecological Life Support System Alternative (MELiSSA). Rotary cell culture systems (RCCS) and random positioning machines (RPM) were used as SMG analogues. The transcriptional responses of the cultures were elucidated. For CO2-producing C. testosteroni and the tripartite culture, a PermaLifeTM PL-70 cell culture bag mounted on an in-house 3D-printed holder was applied to eliminate air bubble formation during SMG cultivation. Gene expression changes indicated that the fluid dynamics in SMG caused nutrient and O2 limitation. Genes involved in urea hydrolysis and nitrification were minimally affected, while denitrification-related gene expression was increased. The findings highlight potential challenges for nitrogen recovery in space.

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: When macrophytes are growing in the river, the vegetation induces substantial changes to the water quality. Some effects are the result of direct interactions, such as photosynthetic activity or nutrient uptake, whereas others may be attributed to indirect effects of the water plants on hydrodynamics and river processes. This research focused on the direct effect of macrophytes on oxygen dynamics and nutrient cycling. Discharge, macrophyte biomass density, basic water quality, dissolved oxygen and nutrient concentrations were in situ monitored throughout the year in a lowland river (Nete catchment, Belgium). In addition, various processes were investigated in more detail in multiple ex situ experiments. The field and aquaria measurement results clearly demonstrated that aquatic plants can exert considerable impact on dissolved oxygen dynamics in a lowland river. When the river was dominated by macrophytes, dissolved oxygen concentrations varied from 5 to 10 mg l−1. Considering nutrient retention, it was shown that the investigated in-stream macrophytes could take up dissolved inorganic nitrogen (DIN) from the water column at rates of View the MathML source. And DIN fluxes towards the vegetation were found to vary from 0.03 to 0.19 g N ha−1 h−1 in spring and summer. Compared to the measured changes in DIN load over the river stretch, it means that about 313% of the DIN retention could be attributed to direct nitrogen uptake from the water by macrophytes. Yet, the role of macrophytes in rivers should not be underrated as aquatic vegetation also exerts considerable indirect effects that may have a greater impact than the direct fixation of nutrients into the plant biomass.

Abstract: Bamboo is an important component in subtropical and tropical forest communities. The plant has characteristic long lanceolate leaves with parallel venation. Prior studies have shown that the leaf shapes of this plant group can be well described by a simplified version (referred to as SGE-1) of the Gielis equation, a polar coordinate equation extended from the superellipse equation. SGE-1 with only two model parameters is less complex than the original Gielis equation with six parameters. Previous studies have seldom tested whether other simplified versions of the Gielis equation are superior to SGE-1 in fitting empirical leaf shape data. In the present study, we compared a three-parameter Gielis equation (referred to as SGE-2) with the two-parameter SGE-1 using the leaf boundary coordinate data of six bamboo species within the same genus that have representative long lanceolate leaves, with >300 leaves for each species. We sampled 2000 data points at approximately equidistant locations on the boundary of each leaf, and estimated the parameters for the two models. The root–mean–square error (RMSE) between the observed and predicted radii from the polar point to data points on the boundary of each leaf was used as a measure of the model goodness of fit, and the mean percent error between the RMSEs from fitting SGE-1 and SGE-2 was used to examine whether the introduction of an additional parameter in SGE-1 remarkably improves the model’s fitting. We found that the RMSE value of SGE-2 was always smaller than that of SGE-1. The mean percent errors among the two models ranged from 7.5% to 20% across the six species. These results indicate that SGE-2 is superior to SGE-1 and should be used in fitting leaf shapes. We argue that the results of the current study can be potentially extended to other lanceolate leaf shapes.

Abstract: Small stationary diesel engines, like in generator sets, have limited emission control measures and are therefore responsible for 44% of the particulate matter (PM) emissions in the United States. The diesel exhaust composition depends on operating conditions of the combustion engine. Furthermore, the measurements are influenced by the used sampling method. This study examines the effect of engine loading and exhaust gas dilution on the composition of small-scale power generators. These generators are used in different operating conditions than road-transport vehicles, resulting in different emission characteristics. Experimental data were obtained for gaseous volatile organic compounds (VOC) and PM mass concentration, elemental composition and nitrate content. The exhaust composition depends on load condition because of its effect on fuel consumption, engine wear and combustion temperature. Higher load conditions result in lower PM concentration and sharper edged particles with larger aerodynamic diameters. A positive correlation with load condition was found for K, Ca, Sr, Mn, Cu, Zn and Pb adsorbed on PM, elements that originate from lubricating oil or engine corrosion. The nitrate concentration decreases at higher load conditions, due to enhanced nitrate dissociation to gaseous NO at higher engine temperatures. Dilution on the other hand decreases PM and nitrate concentration and increases gaseous VOC and adsorbed metal content. In conclusion, these data show that operating and sampling conditions have a major effect on the exhaust gas composition of small-scale diesel generators. Therefore, care must be taken when designing new experiments or comparing literature results.

Abstract: Gielis curves and surfaces can describe a wide range of natural shapes and they have been used in various studies in biology and physics as descriptive tool. This has stimulated the generalization of widely used computational methods. Here we show that proper normalization of the Levenberg-Marquardt algorithm allows for efficient and robust reconstruction of Gielis curves, including self-intersecting and asymmetric curves, without increasing the overall complexity of the algorithm. Then, we show how complex curves of k-type can be constructed and how solutions to the Dirichlet problem for the Laplace equation on these complex domains can be derived using a semi-Fourier method. In all three methods, descriptive and computational power and efficiency is obtained in a surprisingly simple way.

Abstract: Rhodotorula kratochvilovae has shown to be a promising species for microbial oil production from lignin-derived compounds. Yet, information on R. kratochvilovae’s detoxification and microbial oil production is scarce. This study investigated the growth and microbial oil production on the phenolic-containing effluent from poplar steam explosion and its detoxification with five R. kratochvilovae strains (EXF11626, EXF9590, EXF7516, EXF3697, EXF3471) and compared them with Cutaneotrichosporon oleaginosum. The R. kratochvilovae strains reached a maximum growth rate up to four times higher than C. oleaginosum. Furthermore, all R. kratochvilovae strains generally degraded phenolics more rapidly and to a larger extent than C. oleaginosum. However, the diluted substrate limited the lipid production by all strains as the maximum lipid content and titre were 10.5% CDW and 0.40 g/L, respectively. Therefore, future work should focus on increasing lipid production by using advanced fermentation strategies and stimulating the enzyme excretion by the yeasts for complex substrate breakdown.

Abstract: In order to sustain human life in an isolated environment, an efficient conversion of wasted nutrients to food might become mandatory. This is particularly the case for space missions where resupply from earth or in-situ resource utilization is not possible or desirable. A combination of different technologies is needed to allow full recycling of e.g. nitrogenous compounds in space. In this review, an overview is given of the different essential processes and technologies that enable closure of the nitrogen cycle in Bioregenerative Life Support Systems (BLSS). Firstly, a set of biological and physicochemical refinery stages ensures efficient conversion of waste products into the building blocks, followed by the production of food with a range of biological methods. For each technology, bottlenecks are identified. Furthermore, challenges and outlooks are presented at the integrated system level. Space adaptation and integration deserve key attention to enable the recovery of nitrogen for the production of nutritional food in space, but also in closed loop systems on earth.