Redox behavior of the model catalyst Pd/CeO2-x/Pt(111)

Photoelectron spectroscopy and scanning tunneling microscopy have been used to investigate how the oxidation state of Ce in CeO2-x(111) ultrathin films is influenced by the presence of Pd nanoparticles. Pd induces an increase in the concentration of Ce3+ cations, which is interpreted as charge transfer from Pd to CeO2-x(111) on the basis of DFT+U calculations. Charge transfer from Pd to Ce4+ is found to be energetically favorable even for individual Pd adatoms. These results have implications for our understanding of the redox behavior of ceria-based model catalyst systems.

Improved evaporative flux partitioning and carbon flux in the land surface model JULES: impact on the simulation of land surface processes in temperate Europe

The primary role of land surface models embedded in climate models is to partition surface available energy into upwards, radiative, sensible and latent heat fluxes. Partitioning of evapotranspiration, ET, is of fundamental importance: as a major component of the total surface latent heat flux, ET affects the simulated surface water balance, and related energy balance, and consequently the feedbacks with the atmosphere. In this context it is also crucial to credibly represent the CO2 exchange between ecosystems and their environment. In this study, JULES, the land surface model used in UK weather and climate models, has been evaluated for temperate Europe. Compared to eddy covariance flux measurements, the CO2 uptake by the ecosystem is underestimated and the ET overestimated. In addition, the contribution to ET from soil and intercepted water evaporation far outweighs the contribution of plant transpiration. To alleviate these biases, adaptations have been implemented in JULES, based on key literature references. These adaptations have improved the simulation of the spatio-temporal variability of the fluxes and the accuracy of the simulated GPP and ET, including its partitioning. This resulted in a shift of the seasonal soil moisture cycle. These adaptations are expected to increase the fidelity of climate simulations over Europe. Finally, the extreme summer of 2003 was used as evaluation benchmark for the use of the model in climate change studies. The improved model captures the impact of the 2003 drought on the carbon assimilation and the water use efficiency of the plants. It, however, underestimates the 2003 GPP anomalies. The simulations showed that a reduction of evaporation from the interception and soil reservoirs, albeit not of transpiration, largely explained the good correlation between the carbon and the water fluxes anomalies that was observed during 2003. This demonstrates the importance of being able to discriminate the response of individual component of the ET flux to environmental forcing.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

Friendly amendment: a commentary on Doyle and Ford's proposed re-definition of 'mental model'

Some amendments are proposed to a recent redefinition of the mental model concept in system dynamics. First, externalised, or articulated mental models should not be called cognitive maps; this term has a well established, alternative meaning. Second, there can be mental models of entities not yet existing beyond an individual's mind; the modelling of planned or desired systems is possible and recommended. Third, saying that mental models maintain social systems connects with some exciting research opportunities for system dynamics; however, it is probably an accidental distraction from the intended meaning of the redefinition. These minor criticisms apart, the new definition of mental model of a dynamic system is welcomed as a useful contribution to both research and practice.

Future changes of wind energy potentials over Europe in a large CMIP5 multi-model ensemble

A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

Evaluating and optimizing oral formulations of live bacterial vaccines using a gastro-small intestine model

Gastrointestinal (GI) models that mimic physiological conditions in vitro are important tools for developing and optimizing biopharmaceutical formulations. Oral administration of live attenuated bacterial vaccines (LBV) can safely and effectively promote mucosal immunity but new formulations are required that provide controlled release of optimal numbers of viable bacterial cells, which must survive gastrointestinal transit overcoming various antimicrobial barriers. Here, we use a gastro-small intestine gut model of human GI conditions to study the survival and release kinetics of two oral LBV formulations: the licensed typhoid fever vaccine Vivotif comprising enteric coated capsules; and an experimental formulation of the model vaccine Salmonella Typhimurium SL3261 dried directly onto cast enteric polymer films and laminated to form a polymer film laminate (PFL). Neither formulation released significant numbers of viable cells when tested in the complete gastro-small intestine model. The poor performance in delivering viable cells could be attributed to a combination of acid and bile toxicity plus incomplete release of cells for Vivotif capsules, and to bile toxicity alone for PFL. To achieve effective protection from intestinal bile in addition to effective acid resistance, bile adsorbent resins were incorporated into the PFL to produce a new formulation, termed BR-PFL. Efficient and complete release of 4.4x107 live cells per dose was achieved from BR-PFL at distal intestinal pH, with release kinetics controlled by the composition of the enteric polymer film, and no loss in viability observed in any stage of the GI model. Use of this in vitro GI model thereby allowed rational design of an oral LBV formulation to maximize viable cell release.

How does the use of different road networks effect the optimal location of facilities in rural areas?

The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. Distance measure can vary if the accuracy of the road network varies. The rst aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to nd an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an asymmetrically distributed population, Dalecarlia. The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.

On choice of technique in the Robinson-Solow-Srinivasan model

We report results on the optimal \choice of technique" in a model originally formulated by Robinson, Solow and Srinivasan (henceforth, the RSS model) and further discussed by Okishio and Stiglitz. By viewing this vintage-capital model without discounting as a speci c instance of the general theory of intertemporal resource allocation associated with Brock, Gale and McKenzie, we resolve longstanding conjectures in the form of theorems on the existence and price support of optimal paths, and of conditions suÆcient for the optimality of a policy rst identi ed by Stiglitz. We dispose of the necessity of these conditions in surprisingly simple examples of economies in which (i) an optimal path is periodic, (ii) a path following Stiglitz' policy is bad, and (iii) there is optimal investment in di erent vintages at di erent times. (129 words)

On a uniform turnpike of the third kind in the Robinson-Solow-Srinivasan model

On using McKenzie’s taxonomy of optimal accumulation in the longrun, we report a “uniform turnpike” theorem of the third kind in a model original to Robinson, Solow and Srinivasan (RSS), and further studied by Stiglitz. Our results are presented in the undiscounted, discrete-time setting emphasized in the recent work of Khan-Mitra, and they rely on the importance of strictly concave felicity functions, or alternatively, on the value of a “marginal rate of transformation”, ξσ, from one period to the next not being unity. Our results, despite their specificity, contribute to the methodology of intertemporal optimization theory, as developed in economics by Ramsey, von Neumann and their followers.

Optimal taxation with gradual learning of types

An important feature of life-cycle models is the presence of uncertainty regarding one’s labor income. Yet this issue, long recognized in different areas, has not received enough attention in the optimal taxation literature. This paper is an attempt to fill this gap. We write a simple 3 period model where agents gradually learn their productivities. In a framework akin to Mirrlees’ (1971) static one, we derive properties of optimal tax schedules and show that: i) if preferences are (weakly) separable, uniform taxation of goods is optimal, ii) if they are (strongly) separable capital income is to rate than others forms of investiment.

The macroeconomic effects of infrequent information with adjustment costs

We extend the macroeconomic literature on Sstype rules by introducing infrequent information in a kinked ad justment cost model. We first show that optimal individual decision rules are both state-and -time dependent. We then develop an aggregation framework to study the macroeconomic implications of such optimal individual decision rules. In our model, a vast number of agents act together, and more so when uncertainty is large.The average effect of an aggregate shock is inversely related to its size and to aggregate uncertainty. These results are in contrast with those obtained with full information ad justment cost models.

Moral hazard and nonlinear pricing in a general equilibrium model

The paper analyzes a two period general equilibrium model with individual risk and moral hazard. Each household faces two individual states of nature in the second period. These states solely differ in the household's vector of initial endowments, which is strictly larger in the first state (good state) than in the second state (bad state). In the first period households choose a non-observable action. Higher leveis of action give higher probability of the good state of nature to occur, but lower leveIs of utility. Households have access to an insurance market that allows transfer of income across states of oature. I consider two models of financiaI markets, the price-taking behavior model and the nonlínear pricing modelo In the price-taking behavior model suppliers of insurance have a belief about each household's actíon and take asset prices as given. A variation of standard arguments shows the existence of a rational expectations equilibrium. For a generic set of economies every equilibrium is constraíned sub-optímal: there are commodity prices and a reallocation of financiaI assets satisfying the first period budget constraint such that, at each household's optimal choice given those prices and asset reallocation, markets clear and every household's welfare improves. In the nonlinear pricing model suppliers of insurance behave strategically offering nonlinear pricing contracts to the households. I provide sufficient conditions for the existence of equilibrium and investigate the optimality properties of the modeI. If there is a single commodity then every equilibrium is constrained optimaI. Ir there is more than one commodity, then for a generic set of economies every equilibrium is constrained sub-optimaI.

Development of site-specific sediment quality guidelines for North and South Atlantic littoral zones: Comparison against national and international sediment quality benchmarks

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Security constrained optimal active power flow via network model and interior point method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming

In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.