Abstract: Preston's equation is a general model describing the egg shape of birds. The parameters of Preston's equation are usually estimated after re-expressing it as the Todd-Smart equation and scaling the egg's actual length to two. This method assumes that the straight line through the two points on an egg's profile separated by the maximum distance (i.e., the longest axis of an egg's profile) is the mid-line. It hypothesizes that the photographed egg's profile is perfectly bilaterally symmetrical, which seldom holds true because of photographic errors and placement errors. The existing parameter estimation method for Preston's equation considers an angle of deviation for the longest axis of an egg's profile from the mid-line, which decreases prediction errors to a certain degree. Nevertheless, this method cannot provide an accurate estimate of the coordinates of the egg's center, and it leads to sub-optimal parameter estimation. Thus, it is better to account for the possible asymmetry between the two sides of an egg's profile along its mid-line when fitting egg-shape data. In this paper, we propose a method based on the optimization algorithm (optimPE) to fit egg-shape data and better estimate the parameters of Preston's equation by automatically searching for the optimal mid-line of an egg's profile and testing its validity using profiles of 59 bird eggs spanning a wide range of existing egg shapes. We further compared this method with the existing one based on multiple linear regression (lmPE). This study demonstrated the ability of the optimPE method to estimate numerical values of the parameters of Preston's equation and provide the theoretical egg length (i.e., the distance between two ends of the mid-line of an egg's profile) and the egg's maximum breadth. This provides a valuable approach for comparing egg shapes among conspecifics or across different species, or even different classes (e.g., birds and reptiles), in future investigations.

Abstract: This work contributes to a new generalized empirical correlation for predicting methane (CH4) hydrate equilibrium conditions in pure water. Unlike the conventional thermodynamic approach that involves complex reckoning, the proposed empirical equation is developed by regressing 215 experimental data points from the literature and validating with 45 data points for predicting methane hydrate equilibrium conditions in pure water. The new correlation is proposed for a temperature and pressure range of 273.2–303.48 K and 2.63–72.26 MPa, respectively. The accuracy and performance of the proposed correlation is quantitatively evaluated using statistical error analysis. The proposed correlation was able to estimate CH4 hydrate equilibrium conditions satisfactorily with an R2 of 0.99987. The overall error analysis for the proposed correlation shows fair agreement with the experimental data reported within the literature. Concurrently, the new correlation showed better performance in predicting equilibrium conditions compared to those calculated by other empirical correlations available in the literature within the investigated range. In addition, the proposed empirical equation is also checked to evaluate its efficacy in fitting each set of experimental binary/ternary methane hydrates (BTMH) and binary hydrogen hydrates (BHH) for an accurate representation of equilibrium data over a wide range of composition, pressure, and temperature conditions. A maximum percentage deviation of 0.58% and 0.24% was observed between experimental and calculated equilibrium conditions for BTMH and BHH, respectively.

Abstract: Large river catchments with mixed land use capture pesticides from many sources, and degradable pesticides are converted during downstream transport. Unravelling the contribution of pesticide source and the effect of degradation processes is a challenge in such areas. However, insight and understanding of the sources is important for targeted managen-lent, especially when water is abstracted from the river for drinking water production. The river Meuse is such a case. A long-term monitoring data set was applied in a modelling approach for assessing the contribution of waste water treatment plants (WWTPs) and tributaries (sub-basins) to surface water contamination, and to evaluate the effect of decay on the downstream concentrations of glyphosate and AMPA at the point of drinking water abstraction. The results show that WWTPs are important contributors for glyphosate and AMPA in large river catchments with mixed land uses. In the studied area, the river Meuse in the Netherlands, the relative contribution of WWTP effluents is above 29% for glyphosate and around 12% for AMPA. Local industries are found to be potentially big contributors of AMPA. Glyphosate entering the river system is gradually converted to AMPA and other degradation-productions, which results in downstream loads that are considerably lower than the sum of all influxes. In summer when the travel time is longer due to lower discharge, the first order decay of glyphosate in the river Meuse is estimated to result in about 50% reduction of the downstream glyphosate concentrations over a river stretch of 250 km. The contribution of glyphosate decay to the observed AMPA concentrations ranges between 2% and 10%. Contributions are sensitive to seasonal variations in discharge that influence the concentrations through dilution and degradation. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: A shift from batch processing towards continuous processing is of interest in the pharmaceutical industry. However, this transition requires detailed knowledge and process understanding of all consecutive unit operations in a continuous manufacturing line to design adequate control strategies. This can be facilitated by developing mechanistic models of the multi-phase systems in the process. Since modelling efforts only started recently in this field, uncertainties about the model predictions are generally neglected. However, model predictions have an inherent uncertainty (i.e. prediction uncertainty) originating from uncertainty in input data, model parameters, model structure, boundary conditions and software. In this paper, the model prediction uncertainty is evaluated for a model describing the continuous drying of single pharmaceutical wet granules in a six-segmented fluidized bed drying unit, which is part of the full continuous from-powder-to-tablet manufacturing line (Consigma (TM), GEA Pharma Systems). A validated model describing the drying behaviour of a single pharmaceutical granule in two consecutive phases is used. First of all, the effect of the assumptions at the particle level on the prediction uncertainty is assessed. Secondly, the paper focuses on the influence of the most sensitive parameters in the model. Finally, a combined analysis (particle level plus most sensitive parameters) is performed and discussed. To propagate the uncertainty originating from the parameter uncertainty to the model output, the Generalized Likelihood Uncertainty Estimation (GLUE) method is used. This method enables a modeller to incorporate the information obtained from the experimental data in the assessment of the uncertain model predictions and to find a balance between model performance and data precision. A detailed evaluation of the obtained uncertainty analysis results is made with respect to the model structure, interactions between parameters and uncertainty boundaries. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: The goal of this study is to provide a rigorous tool to quantify the inequality of the leaf size distribution of an individual plant, thereby serving as a reference trait for quantifying plant adaptations to local environmental conditions. The tool to be presented and tested employs three components: (1) a performance equation (PE), which can produce flexible asymmetrical and symmetrical bell-shaped curves, (2) the Lorenz curve (i.e., the cumulative proportion of leaf size vs. the cumulative proportion of number of leaves), which is the basis for calculating, and (3) the Gini index, which measures the inequality of leaf size distribution. We sampled 12 individual plants of a dwarf bamboo and measured the area and dry mass of each leaf of each plant. We then developed a generalized performance equation (GPE) of which the PE is a special case and fitted the Lorenz curve to leaf size distribution using the GPE and PE. The GPE performed better than the PE in fitting the Lorenz curve. We compared the Gini index of leaf area distribution with that of leaf dry mass distribution and found that there was a significant difference between the two indices that might emerge from the scaling relationship between leaf dry mass and area. Nevertheless, there was a strong correlation between the two Gini indices (r2 = 0.9846). This study provides a promising tool based on the GPE for quantifying the inequality of leaf size distributions across individual plants and can be used to quantify plant adaptations to local environmental conditions.

Abstract: Long-term human Space missions will rely on regenerative life support as resupply of water, oxygen and food comes with constraints. The International Space Station (ISS) relies on an evaporation/condensation system to recover 74–85% of the water in urine, yet suffers from repetitive scaling and biofouling while employing hazardous chemicals. In this study, an alternative non-sanitary five-stage treatment train for one “astronaut” was integrated through a sophisticated monitoring and control system. This so-called Water Treatment Unit Breadboard (WTUB) successfully treated urine (1.2-L-d−1) with crystallisation, COD-removal, ammonification, nitrification and electrodialysis, before it was mixed with shower water (3.4-L-d−1). Subsequently, ceramic nanofiltration and single-pass flat-sheet RO were used. A four-months proof-of-concept period yielded: (i) chemical water quality meeting the hygienic standards of the European Space Agency, (ii) a 87-±-5% permeate recovery with an estimated theoretical primary energy requirement of 0.2-kWhp-L−1, (iii) reduced scaling potential without anti-scalant addition and (iv) and a significant biological reduction in biofouling potential resulted in stable but biofouling-limited RO permeability of 0.5 L-m−2-h−1-bar−1. Estimated mass breakeven dates and a comparison with the ISS Water Recovery System for a hypothetical Mars transit mission show that WTUB is a promising biological membrane-based alternative to heat-based systems for manned Space missions.

Abstract: The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.

Abstract: Heterogeneous photocatalysis can be used as an advanced oxidation technology frequently studied for application in photoreactors for air and water treatment. Extensive experimental investigation entails high costs and is also time consuming. Multiphysics modelling, a relatively new numerical method, provides a cost-effective and valuable alternative. By reconstructing the reactor geometry in dedicated software, meshing it and solving for occurring physical and chemical phenomena, Multiphysics models can be used to evaluate the performance of different reactor designs, increase insight into the occurring phenomena and study the influence of operational parameters on reactor performance. Finally, Multiphysics models are also developed for various applications like optimising the operational parameters, creating the ideal reactor design or scaling up a lab-scale reactor to a realistic prototype.

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: Three-dimensional (3D) computational fluid dynamics (CFD) simulations were performed to study solids flow dynamics and solids back-mixing behavior in a screw reactor (designed for thermal conversion of dry biomass particles) based on the Eulerian-Eulerian method. Simulation results were compared against experimental data with respect to filling degree and mean residence time of particles. The mean deviations for filling degree and for mean residence time between simulation and experiment were about 0.01 and 11.4 s, respectively, which shows that the model is reasonably accurate in predicting solids flow behavior in the screw reactor. The solids flow dynamics inside the reactor were discussed. The solids residence time distribution (RTD) was calculated and the degree of solids back-mixing in the forward transportation direction of the reactor was analyzed. It was found that solids being flung over the shaft and solids back-leakage, resulting from the low solids forward transportation velocity at the clearance between the flight and the bottom shell of the screw reactor, were responsible for solids back-mixing. The degree of solids back-mixing can be reduced at higher screw rotating speeds when keeping inlet mass flow rate of solids constant. (C) 2019 Elsevier Ltd. All rights reserved.