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North Sea fisheries are managed by the European Union (EU) through a system of annual quota. Due to uncertainty about future fish stocks, yearly revisions of these policies lead to fluctuation in quota, which in turn affects harvest and investment decisions of fishermen. Determination of quota requires high management costs in terms of obtaining information and negotiations between experts and policy makers. To reduce both quota fluctuation and management costs, the EU has proposed a system of multiannual quota. In this paper we study the effect of multiannual quota on quota volatility and resource rents, while accounting for management costs. We develop a bi-level stochastic dynamic programming model, where at level one, the EU determines the quota that maximizes resource rents. At level two, fishermen decide myopically on their harvest and investment levels, subject to the quota. Results show that policy makers can reduce quota volatility and improve resource rents from the fishery with multiannual quota. Important trade-offs are involved in the accomplishment of these objectives: fish stock and investments become more volatile, which leads to more overcapacity.

Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO2 concentration, and the maximum amount of CO2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO2 were used as control variables.Standard optimization settings were defined in order to compare the grower's strategy with the optimal solution. This optimization resulted in a theoretical 47% reduction in heating, 15% reduction in cooling, and 10% reduction in CO2 injection for the year 2012. The optimal control does not need to maintain a minimum pipe temperature, in contrast to current practice. When the minimum pipe temperature strategy of the grower was implemented, heating and CO2 were reduced by 28% and 10% respectively.We also analyzed the effect of different bounds on optimal energy input. We found that as more freedom is given to the climate variables, the higher the potential energy savings. However, in practice the grower is in charge of defining the bounds. Thus, the potential energy savings critically depend on the choice of these bounds. This effect was analyzed by varying the bounds. However, because the effect can be demonstrated to the grower, the outcome has value to the grower with respect to decision making, an option that is not currently available in practice today.

<div class="section abstract"><div class="htmlview paragraph">The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO₂-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO₂-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.</div><div class="htmlview paragraph">In this framework, a comprehensive approach covering the whole powertrain is of primary importance in order to simultaneously meet the performance, efficiency, noise and emission targets, and therefore, further development of the combustion system design and injection system represent important levers for additional improvements. For this purpose, a dedicated 0.5 dm³ single-cylinder engine has been developed and equipped with, a state-of-the-art Euro 6 combustion system, and an advanced common rail fuel injection system (FIS) offering higher flexibility in terms of injection strategy and higher quantity accuracy. Three injector nozzles with different hydraulic flow rates (HF) have been selected and employed for the overall combustion process optimization.</div><div class="htmlview paragraph">The optimization has been performed by means of an extensive DoE-based test campaign in which the engine and FIS operating parameters have been parametrized with the aim to carry out a proper combination in terms of HF and injection strategy. The results at partial load conditions evidence significant advantages in applying an advanced injection pattern, while the HF reduction can significantly improve the smoke emission and combustion noise without fuel consumption penalties. Therefore, a proper combination and optimization of the HF and injection strategy can provide low noise and engine-out smoke while maintaining the rated power performance targets.</div></div>

AbstractThe surface oxygen exchange on oxides with high oxygen ion mobility is modelled with a two step reaction with adsorbed mono-atomic oxygen species as intermediate. Interpretation of the Po2 dependence of the exchange rates, following from this model, indicates that these adsorbed oxygen atoms are singly charged.For the stabilized δ-Bi2O3 solid electrolyte a good agreement has been found between the isotope exchange model and the electrochemical study of the oxygen exchange using gold electrodes. For the mixed La-Sr cobaltite perovskite a change in the surface exchange reaction is observed going from room temperature to 600°C. Indications are that above 450°C the bulk exchange is rate limiting with a (Po2)−1 dependence while below this temperature it is assumed that the dissociative adsorption is rate limiting with a (Po2)1/2 dependence.

A good process understanding is the foundation for process optimization, process monitoring, end-point detection, and estimation of the end-product quality. Performing good process measurements and the construction of process models will contribute to a better process understanding. To improve the process knowledge it is common to build process models. These models are often based on first principles such as kinetic rates or mass balances. These types of models are also known as hard or white models. White models are characterized by being generally applicable but often having only a reasonable fit to real process data. Other commonly used types of models are empirical or black-box models such as regression and neural nets. Black-box models are characterized by having a good data fit but they lack a chemically meaningful model interpretation. Alternative models are grey models, which are combinations of white models and black models. The aim of a grey model is to combine the advantages of both black-box models and white models. In a qualitative case study of monitoring industrial batches using near-infrared (NIR) spectroscopy, it is shown that grey models are a good tool for detecting batch-to-batch variations and an excellent tool for process diagnosis compared to common spectroscopic monitoring tools.

Plant-soil feedback (PSF) describes the process whereby plant species modify the soil environment, which subsequently impacts the growth of the same or another plant species. Our aim was to explore PSF by two maize varieties (a landrace and a hybrid variety) and three arbuscular mycorrhizal fungi (AMF) species (Funneliformis mosseae, Claroideoglomus etunicatum, Gigaspora margarita, and the mixture). We carried out a pot experiment with a conditioning and a feedback phase to determine PSF with different species of AMF and with a non-mycorrhizal control. Sterilized soil was conditioned separately by each variety, with or without AMF; in the feedback phase, each soil community was used to grow each in its "home" soil and in the "away" soil. Plant performance was assessed as shoot biomass, phosphorus (P) concentration and P content, and fungal performance was assessed as mycorrhizal colonization and hyphal length density. Both maize varieties were differentially influenced by AMF in the conditioning phase. In the feedback phase, PSF was generally negative for non-mycorrhizal plants or when plants were colonized by G. margarita, whereas PSF was positive in the other three AMF treatments. When plants were grown on home soil, hyphal length density was larger than on away soil. We conclude that different maize varieties can strengthen positive plant-soil feedback for themselves through beneficial mutualists for themselves, but not across the maize varieties.