Regular wave propagation out of noise in chemical active media

A pacemaker, regularly emitting chemical waves, is created out of noise when an excitable photosensitive Belousov-Zhabotinsky medium, strictly unable to autonomously initiate autowaves, is forced with a spatiotemporal patterned random illumination. These experimental observations are also reproduced numerically by using a set of reaction-diffusion equations for an activator-inhibitor model, and further analytically interpreted in terms of genuine coupling effects arising from parametric fluctuations. Within the same framework we also address situations of noise-sustained propagation in subexcitable media.

Regular population monotonic allocation schemes and the core

A subclass of games with population monotonic allocation schemes is studied, namelygames with regular population monotonic allocation schemes (rpmas). We focus on theproperties of these games and we prove the coincidence between the core and both theDavis-Maschler bargaining set and the Mas-Colell bargaining set

Duas crianças cegas congênitas no primeiro ciclo da escola regular

O estudo tem como objetivo investigar com maior profundidade a pesquisa sobre representação mental da realidade em crianças com cegueira congênita, comparando-as com crianças normovisuais no ensino básico da escola regular em Portugal. A partir de fundamentos teóricos, pretende-se analisar as diferentes crianças ao longo do tempo, bem como a sociedade atual perante as crianças diferentes. Foram feitos dois estudos de caso, combinando dados de natureza quantitativa e qualitativa. A análise desses casos revela dois caminhos diferentes na integração de crianças com cegueira congênita no primeiro ciclo do ensino básico, sendo que essa diferenciação não resulta dos processos de adaptação ao aluno concreto numa perspectiva humanista e, sim, dos condicionamentos físicos (escolas) e organizacionais (Educação Especial).

Regular wave propagation out of noise in chemical active media

A pacemaker, regularly emitting chemical waves, is created out of noise when an excitable photosensitive Belousov-Zhabotinsky medium, strictly unable to autonomously initiate autowaves, is forced with a spatiotemporal patterned random illumination. These experimental observations are also reproduced numerically by using a set of reaction-diffusion equations for an activator-inhibitor model, and further analytically interpreted in terms of genuine coupling effects arising from parametric fluctuations. Within the same framework we also address situations of noise-sustained propagation in subexcitable media.

The effect of regular collection of Drosera rotundifolia in natural peatlands in Finland: plant density, yield and regeneration

Tiivistelmä

Assessing the Costs for Hybrid versus Regular Transit Buses, October 2012

This technical brief summarizes information about the costs and benefits that have been attributed to use of hybrid transit buses as found in the literature. Results from a demonstration project that compared fuel economy and emissions for 12 hybrid buses and 7 control buses for the transit agency for Ames, Iowa and Iowa State University, CyRide, were also included.

Evaluation of In-Use Fuel Economy and On-Board Emissions for Hybrid and Regular CyRide Transit Buses, October 2012

The objective of this project was to evaluate the in-use fuel economy and emission differences between hybrid-electric and conventional transit buses for the Ames, Iowa transit authority, CyRide. These CyRide buses were deployed in the fall of 2010. Fuel economy was compared for the hybrid and control buses. Several older bus types were also available and were included in the analysis. Hybrid buses had the highest fuel economy for all time periods for all bus types. Hybrid buses had a fuel economy that was 11.8 percent higher than control buses overall, 12.2 percent higher than buses with model years 2007 and newer, 23.4 percent higher than model years 2004 through 2006, 10.2 percent higher than model years 1998 through 2003, 38.1 percent higher than model years 1994 through 1997, 36.8 percent higher than model years 1991 through 1993, and 36.8 percent higher for model years pre-1991. On-road emissions were also compared for three of the hybrid buses and two control buses using a portable emissions monitor. On-average, carbon dioxide, carbon monoxide, and hybrid carbon emissions were much higher for the control buses than for the hybrid buses. However, on average nitrogen oxide emissions were higher for the hybrid buses.

Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models

Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.

Carbohydrate and nitrogen stores in Festuca paniculata under mowing explain dominance in subalpine grasslands

Cessation of traditional management threatens semi-natural grassland diversity through the colonisation or increase of competitive species adapted to nutrient-poor conditions. Regular mowing is one practice that controls their abundance. This study evaluated the ecophysiological mechanisms limiting short- and long-term recovery after mowing for Festuca paniculata, a competitive grass that takes over subalpine grasslands in the Alps following cessation of mowing. We quantified temporal variations in carbon (C) and nitrogen (N) content, starch, fructan and total soluble sugars in leaves, stem bases and roots of F. paniculata during one growth cycle in mown and unmown fields and related them to the dynamics of soil mineral N concentration and soil moisture. Short-term results suggest that the regrowth of F. paniculata following mowing might be N-limited, first because of N dilution by C increments in the plant tissue, and second, due to low soil mineral N and soil moisture at this time of year. However, despite short-term effects of mowing on plant growth, C and N content and concentration at the beginning of the following growing season were not affected. Nevertheless, total biomass accumulation at peak standing biomass was largely reduced compared to unmown fields. Moreover, lower C storage capacity at the end of the growing season impacted C allocation to vegetative reproduction during winter, thereby dramatically limiting the horizontal growth of F. paniculata tussocks in the long term. We conclude that mowing reduces the growth of F. paniculata tussocks through both C and N limitation. Such results will help understanding how plant responses to defoliation regulate competitive interactions within plant communities.

Deep learning via semi-supervised embedding

We show how nonlinear embedding algorithms popular for use with shallow semi-supervised learning techniques such as kernel methods can be applied to deep multilayer architectures, either as a regularizer at the output layer, or on each layer of the architecture. This provides a simple alternative to existing approaches to deep learning whilst yielding competitive error rates compared to those methods, and existing shallow semi-supervised techniques.