Predicting polarization enhancement in multicomponent ferroelectric superlattices

Ab initio calculations are utilized as an input to develop a simple model of polarization in epitaxial short-period CaTiO3/SrTiO3/BaTiO3 superlattices grown on a SrTiO3 substrate. The model is then combined with a genetic algorithm technique to optimize the arrangement of individual CaTiO3, SrTiO3 and BaTiO3 layers in a superlattice, predicting structures with the highest possible polarization and a low in-plane lattice constant mismatch with the substrate. This modelling procedure can be applied to a wide range of layered perovskite-oxide nanostructures providing guidance for experimental development of nanoelectromechanical devices with substantially improved polar properties.Comment: 4 pages, submitted to PR

Properties of Nucleon Resonances by means of a Genetic Algorithm

We present an optimization scheme that employs a Genetic Algorithm (GA) to determine the properties of low-lying nucleon excitations within a realistic photo-pion production model based upon an effective Lagrangian. We show that with this modern optimization technique it is possible to reliably assess the parameters of the resonances and the associated error bars as well as to identify weaknesses in the models. To illustrate the problems the optimization process may encounter, we provide results obtained for the nucleon resonances $\Delta$(1230) and $\Delta$(1700). The former can be easily isolated and thus has been studied in depth, while the latter is not as well known experimentally.Comment: 12 pages, 10 figures, 3 tables. Minor correction

High elevation watersheds in the southern Appalachians: Indicators of sensitivity to acidic deposition and the potential for restoration through liming

Southern Appalachian high elevation watersheds have deep rocky soils with high organic matter content, different vegetation communities, and receive greater inputs of acidic deposition compared to low elevation sites within the region. Since the implementation of the Clean Air Act Amendment in the 1990s, concentrations of acidic anions in rainfall have declined. However, some high elevation streams continue to show signs of chronic to episodic acidity, where acid neutralizing capacity (ANC) ranges from 0 to 20 µeq L-1. We studied three 3rd order watersheds (North River in Cherokee National Forest, Santeetlah Creek in Nantahala National Forest, and North Fork of the French Broad in Pisgah National Forest) and selected four to six 1st order catchments within each watershed to represent a gradient in elevation (849–1526 m) and a range in acidic stream ANC values (11–50 leq L-1). Our objectives were to (1) identify biotic, physical and chemical catchment parameters that could be used as indices of stream ANC, pH and Ca:Al molar ratios and (2) estimate the lime required to restore catchments from the effects of excess acidity and increase base cation availability. We quantified each catchment’s biotic, physical, and chemical characteristics and collected stream, O-horizon, and mineral soil samples for chemical analysis seasonally for one year. Using repeated measures analysis, we examined variability in stream chemistry and catchment characteristics; we used a nested split-plot design to identify catchment characteristics that were correlated with stream chemistry. Watersheds differed significantly and the catchments sampled provided a wide range of stream chemical, biotic, physical and chemical characteristics. Variability in stream ANC, pH, and Ca:Al molar ratio were significantly correlated with catchment vegetation characteristics (basal area, tree height, and tree diameter) as well as O-horizon nitrogen and aluminum concentrations. Total soil carbon and calcium (an indicator of parent material), were significant covariates for stream ANC, pH and Ca:Al molar ratios. Lime requirement estimates did not differ among watersheds but this data will help select catchments for future restoration and lime application studies. Not surprisingly, this work found many vegetation and chemical characteristics that were useful indicators of stream acidity. However, some expected relationships such as concentrations of mineral soil extractable Ca and SO4 were not significant. This suggests that an extensive test of these indicators across the southern Appalachians will be required to identify high elevation forested catchments that would benefit from restoration activities

A Model for Analysing the Collective Dynamic Behaviour and Characterising the Exploitation of Population-Based Algorithms

Several previous studies have focused on modelling and analysing the collective dynamic behaviour of population-based algorithms. However, an empirical approach for identifying and characterising such a behaviour is surprisingly lacking. In this paper, we present a new model to capture this collective behaviour, and to extract and quantify features associated with it. The proposed model studies the topological distribution of an algorithm's activity from both a genotypic and a phenotypic perspective, and represents population dynamics using multiple levels of abstraction. The model can have different instantiations. Here it has been implemented using a modified version of self-organising maps. These are used to represent and track the population motion in the fitness landscape as the algorithm operates on solving a problem. Based on this model, we developed a set of features that characterise the population's collective dynamic behaviour. By analysing them and revealing their dependency on fitness distributions, we were then able to define an indicator of the exploitation behaviour of an algorithm. This is an entropy-based measure that assesses the dependency on fitness distributions of different features of population dynamics. To test the proposed measures, evolutionary algorithms with different crossover operators, selection pressure levels and population handling techniques have been examined, which lead populations to exhibit a wide range of exploitation-exploration behaviours. </jats:p