A eficacia e a heterocronia das respostas de adaptação de basquetebolistas submetidos a diferentes modelos de estruturação da carga de treinamento e competição

Universidade Estadual de Campinas . Faculdade de Educação Física

Risk adjustment in Switzerland

In Switzerland the new law on Health Insurance, effective since 1996, introduced pro competitive changes in the market of sickness funds. The legislator expected high mobility between sickness funds of both healthy and sick insured as open enrolment was introduced with the new law. That is why the risk adjustment scheme, that was already introduced 1993, was limited until 2005. However, consumer mobility remained low and risk selection strategies are still profitable, since risk-adjustment is based only on demographic variables. This paper describes risk adjustment, consumer mobility, risk selection activities of sickness funds and the impact of imperfect risk adjustment on the development of HMO and PPO models. The paper concludes with a description of the current political and scientific discussion in Switzerland.

Managing arable weeds for biodiversity

As a result of the recent intensification of crop production, the abundance and diversity of UK arable weeds adapted to cultivated land have declined, with an associated reduction in farmland birds. A number of questions need to be addressed when considering how these declines can be reversed. Firstly, can the delivery of crop production and biodiversity be reconciled by spatially separating cropping from designated wildlife areas? A number of subsidised environmental schemes in the UK take this approach and are focused on establishing vegetation cover on uncropped land. However, because of the lack of regular disturbance in these habitats, they are dominated by perennials and they therefore have limited potential for promoting the recovery of annual weed populations. A number of farmland bird species also rely on the provision of resources in field centres, and it is therefore likely that the recovery of their populations will rely on weed management options targeted at the cropped areas of the field. This raises two further questions. Firstly, is it possible to identify beneficial weed species that are relatively poor competitors with the crop and also have biodiversity value? Secondly, are the tools available to manage these species at acceptable levels while controlling pernicious weeds? A number of approaches are being employed to answer these questions, including predicting yield loss from weed competition models and exploiting herbicide selectivity. The further development of these tools is crucial if farmer opposition to managing weeds in crops is to be overcome. (c) 2007 Society of Chemical Industry.

Nonautonomous difference equations with applications

This work is divided in two parts. In the first part we develop the theory of discrete nonautonomous dynamical systems. In particular, we investigate skew-product dynamical system, periodicity, stability, center manifold, and bifurcation. In the second part we present some concrete models that are used in ecology/biology and economics. In addition to developing the mathematical theory of these models, we use simulations to construct graphs that illustrate and describe the dynamics of the models. One of the main contributions of this dissertation is the study of the stability of some concrete nonlinear maps using the center manifold theory. Moreover, the second contribution is the study of bifurcation, and in particular the construction of bifurcation diagrams in the parameter space of the autonomous Ricker competition model. Since the dynamics of the Ricker competition model is similar to the logistic competition model, we believe that there exists a certain class of two-dimensional maps with which we can generalize our results. Finally, using the Brouwer’s fixed point theorem and the construction of a compact invariant and convex subset of the space, we present a proof of the existence of a positive periodic solution of the nonautonomous Ricker competition model.

A teoria de Norbert Elias: uma análise do ser professor

No presente artigo, conforme o entendimento de que modelos te- óricos subsidiam a compreensão de fenômenos investigativos, objetivou-se elucidar os conceitos da teoria sociológica de Norbert Elias, considerando-se que esta é uma excelente fonte de análise para se compreender o universo do ser professor, apesar de o autor não abordar diretamente questões relacionadas ao campo da educação. A partir do conceito de configuração, é possível dizer que a constituição do ser professor resulta das diferentes configurações nas quais ele está imerso, pois, de acordo com Elias, as pessoas (professores, pais, gestores, ministros, alunos etc.) modelam suas ideias a partir de todas as suas experiências e, essencialmente, das experiências vividas no interior do próprio grupo. É observável que as configurações, formadas por grupos interdependentes de pessoas, e não por indivíduos singulares, apresentam-se cada vez mais ampliadas nos contextos escolares, com funções especializadas e específicas (professores, alunos, diretores, coordenadores, supervisores, secretários etc.), em grupos que se tornam cada vez mais funcionalmente dependentes. As cadeias de interdependência estão mais diferenciadas e, consequentemente, mais opacas e dificilmente controláveis por parte de quaisquer grupos ou indiví- duos. Portanto, uma melhor compreensão será possível quando se estudar empiricamente as configurações que estão em jogo na educação brasileira. Daí se justifica a análise das configurações e das teias de interdependência em que os professores estão envolvidos. Enfim, a aplicação dos modelos de competição abordados por Elias possibilita evidenciar as problemáticas sociológicas do ser professor, tornando-as mais evidentes e facilitando o entendimento do jogo para reorganizá-lo em termos de equilíbrio na teia social.

Intraspecific Aggregation Alters Competitive Interactions in Experimental Plant Communities

We tested the prediction from spatial competition models that intraspecific aggregation may promote coexistence and thus maintain biodiversity with experimental communities of four annual species. Monocultures, three-species mixtures, and the four-species mixture were sown at two densities and with either random or intraspecifically aggregated distributions. There was a hierarchy of competitive abilities among the four species. The weaker competitors showed higher aboveground biomass in the aggregated distribution compared to the random distribution, especially at high density. In one species, intraspecific aggregation resulted in an 86% increase in the number of flowering individuals and a 171% increase in the reproductive biomass at high density. The competitively superior species had a lower biomass in the aggregated distribution than in the random distribution at high density. The data support the hypothesis that the spatial distribution of plants profoundly affects competition in such a way that weaker competitors increase their fitness while stronger competitors are suppressed when grown in the neighborhood of conspecifics. This implies that the spatial arrangement of plants in a community can be an important determinant of species coexistence and biodiversity.

Multiplant strategy under core-periphery structure

A typical implicit assumption on monopolistic competition models for trade and economic geography is that firms can produce and sell only at one place. This paper fallows endogenous determination of the number of plants in a new economic geography model and examine the stable outcomes of organization choice between single-plant and multi-plant in two regions. We explicitly consider the firms' trade-off between larger economies of scale under single plant configuration and the saving in interregional transport costs under multi-plant configuration. We show that organization change arises under decreasing transportation costs and observe several organization configurations under a generalized cost function.

Using simulation models to investigate the cumulative effects of sowing rate, sowing date and cultivar choice on weed competition

With the increasing pressure on crop production from the evolution of herbicide resistance, farmers are increasingly adopting Integrated Weed Management (IWM) strategies to augment their weed control. These include measures to increase the competitiveness of the crop canopy such as increased sowing rate and the use of more competitive cultivars. While there are data on the relative impact of these non-chemical weed control methods assessed in isolation, there is uncertainty about their combined contribution, which may be hindering their adoption. In this article, the INTERCOM simulation model of crop / weed competition was used to examine the combined impact of crop density, sowing date and cultivar choice on the outcomes of competition between wheat (Triticum aestivum) and Alopecurus myosuroides. Alopecurus myosuroides is a problematic weed of cereal crops in North-Western Europe and the primary target for IWM in the UK because it has evolved resistance to a range of herbicides. The model was parameterised for two cultivars with contrasting competitive ability, and simulations run across 10 years at different crop densities and two sowing dates. The results suggest that sowing date, sowing density and cultivar choice largely work in a complementary fashion, allowing enhanced competitive ability against weeds when used in combination. However, the relative benefit of choosing a more competitive cultivar decreases at later sowing dates and higher crop densities. Modelling approaches could be further employed to examine the effectiveness of IWM, reducing the need for more expensive and cumbersome long-term in situ experimentation.

Models of privatization and development of competition in telecommunications in Central America and Mexico

Incluye Bibliografía

Models of immune memory: On the role of cross-reactive stimulation, competition, and homeostasis in maintaining immune memory

There has been much debate on the contribution of processes such as the persistence of antigens, cross-reactive stimulation, homeostasis, competition between different lineages of lymphocytes, and the rate of cell turnover on the duration of immune memory and the maintenance of the immune repertoire. We use simple mathematical models to investigate the contributions of these various processes to the longevity of immune memory (defined as the rate of decline of the population of antigen-specific memory cells). The models we develop incorporate a large repertoire of immune cells, each lineage having distinct antigenic specificities, and describe the dynamics of the individual lineages and total population of cells. Our results suggest that, if homeostatic control regulates the total population of memory cells, then, for a wide range of parameters, immune memory will be long-lived in the absence of persistent antigen (T1/2 > 1 year). We also show that the longevity of memory in this situation will be insensitive to the relative rates of cross-reactive stimulation, the rate of turnover of immune cells, and the functional form of the term for the maintenance of homeostasis.

Agent Based Models of Competition and Collaboration

Swarm intelligence is a popular paradigm for algorithm design. Frequently drawing inspiration from natural systems, it assigns simple rules to a set of agents with the aim that, through local interactions, they collectively solve some global problem. Current variants of a popular swarm based optimization algorithm, particle swarm optimization (PSO), are investigated with a focus on premature convergence. A novel variant, dispersive PSO, is proposed to address this problem and is shown to lead to increased robustness and performance compared to current PSO algorithms. A nature inspired decentralised multi-agent algorithm is proposed to solve a constrained problem of distributed task allocation. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. New rules for specialisation are proposed and are shown to exhibit improved eciency and exibility compared to existing ones. These new rules are compared with a market based approach to agent control. The eciency (average number of tasks performed), the exibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved eciency and robustness. Evolutionary algorithms are employed, both to optimize parameters and to allow the various rules to evolve and compete. We also observe extinction and speciation. In order to interpret algorithm performance we analyse the causes of eciency loss, derive theoretical upper bounds for the eciency, as well as a complete theoretical description of a non-trivial case, and compare these with the experimental results. Motivated by this work we introduce agent "memory" (the possibility for agents to develop preferences for certain cities) and show that not only does it lead to emergent cooperation between agents, but also to a signicant increase in efficiency.

COMPETITION AMONG EUCALYPTUS TREES DEPENDS ON GENETIC VARIATION AND RESOURCE SUPPLY

Genetic variation and environmental heterogeneity fundamentally shape the interactions between plants of the same species. According to the resource partitioning hypothesis, competition between neighbors intensifies as their similarity increases. Such competition may change in response to increasing supplies of limiting resources. We tested the resource partitioning hypothesis in stands of genetically identical (clone-origin) and genetically diverse (seed-origin) Eucalyptus trees with different water and nutrient supplies, using individual-based tree growth models. We found that genetic variation greatly reduced competitive interactions between neighboring trees, supporting the resource partitioning hypothesis. The importance of genetic variation for Eucalyptus growth patterns depended strongly on local stand structure and focal tree size. This suggests that spatial and temporal variation in the strength of species interactions leads to reversals in the growth rank of seed-origin and clone-origin trees. This study is one of the first to experimentally test the resource partitioning hypothesis for intergenotypic vs. intragenotypic interactions in trees. We provide evidence that variation at the level of genes, and not just species, is functionally important for driving individual and community-level processes in forested ecosystems.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.