The role of self-teaching in learning orthographic and semantic aspects of new words

This study explores how children learn the meaning (semantics) and spelling patterns (orthography) of novel words encountered in story context. English-speaking children (N = 88) aged 7 to 8 years read 8 stories and each story contained 1 novel word repeated 4 times. Semantic cues were provided by the story context such that children could infer the meaning of the word (specific context) or the category that the word belonged to (general context). Following story reading, posttests indicated that children showed reliable semantic and orthographic learning. Decoding was the strongest predictor of orthographic learning, indicating that self-teaching via phonological recoding was important for this aspect of word learning. In contrast, oral vocabulary emerged as the strongest predictor of semantic learning.

Normative, systemic and procedural aspects: a review of indicator-based sustainability assessments in agriculture

Methods for assessing the sustainability of agricultural systems do often not fully (i) take into account the multifunctionality of agriculture, (ii) include multidimensionality, (iii) utilize and implement the assessment knowledge and (iv) identify conflicting goals and trade-offs. This chapter reviews seven recently developed multidisciplinary indicator-based assessment methods with respect to their contribution to these shortcomings. All approaches include (1) normative aspects such as goal setting, (2) systemic aspects such as a specification of scale of analysis and (3) a reproducible structure of the approach. The approaches can be categorized into three typologies: first, top-down farm assessments, which focus on field or farm assessment; second, top-down regional assessments, which assess the on-farm and the regional effects; and third, bottom-up, integrated participatory or transdisciplinary approaches, which focus on a regional scale. Our analysis shows that the bottom-up, integrated participatory or transdisciplinary approaches seem to better overcome the four shortcomings mentioned above.

Spatial-temporal aspects of cost-benefit analysis for park management: an example from Khao Yai National Park, Thailand

Using a model calibrated to Khao Yai National Park in Thailand, this paper highlights the importance of generating explicitly spatial and temporal data for developing management plans for tropical protected forests. Spatial and temporal cost-benefit analysis should account for the interactions between different land uses – such as the benefits of contiguous areas of preserved land and edge effects – and the realities of villagers living near forests who rely on extracted resources. By taking a temporal perspective, this paper provides a rare empirical assessment of the importance of quasi-option values when determining optimal management plans.

A complex system perspective on the emergence and spread of infectious diseases: integrating economic and ecological aspects

The emergence and spread of infectious diseases reflects the interaction of ecological and economic factors within an adaptive complex system. We review studies that address the role of economic factors in the emergence and spread of infectious diseases and identify three broad themes. First, the process of macro-economic growth leads to environmental encroaching, which is related to the emergence of infectious diseases. Second, there are a number of mutually reinforcing processes associated with the emergence/spread of infectious diseases. For example, the emergence and spread of infectious diseases can cause significant economic damages, which in turn may create the conditions for further disease spread. Also, the existence of a mutually reinforcing relationship between global trade and macroeconomic growth amplifies the emergence/spread of infectious diseases. Third, microeconomic approaches to infectious disease point to the adaptivity of human behavior, which simultaneously shapes the course of epidemics and responds to it. Most of the applied research has been focused on the first two aspects, and to a lesser extent on the third aspect. With respect to the latter, there is a lack of empirical research aimed at characterizing the behavioral component following a disease outbreak. Future research should seek to fill this gap and develop hierarchical econometric models capable of integrating both macro and micro-economic processes into disease ecology.

Game-theoretic aspects of international mergers: Theory and case studies

This paper studies the exclusion of potential competition as a motivating factor for international mergers. We propose a simple game-theoretic framework in order to discuss the conditions under which mergers that prevent reciprocal domestic competition will occur. Our analysis highlights the shortcomings of antitrust policies based on pre-merger/post-merger concentration comparisons. A review of several recent European cases suggests that actual merger policy often fails to consider potential competition.

Cross-cultural generality and specificity in self-regulation: avoidance personal goals and multiple aspects of well-being in the United States and Japan

The authors examined avoidance personal goals as concurrent (Study 1) and longitudinal (Study 2) predictors of multiple aspects of well-being in the United States and Japan. In both studies, participants adopted more avoidance personal goals in Japan relative to the United States. Both studies also demonstrated that avoidance personal goals were significant negative predictors of the most relevant aspects of well-being in each culture. Specifically, avoidance personal goals were negative predictors of intrapersonal and eudaimonic well-being in the United States and were negative predictors of interpersonal and eudaimonic well-being in Japan. The findings clarify and extend puzzling findings from prior empirical work in this area, and raise provocative possibilities about the nature of avoidance goal pursuit.

Aspects of in vitro and in vivo research approaches directed towards identifying probiotics and prebiotics for human use

The microbiota of the human gastrointestinal tract plays a key role in nutrition and health. Through the process of fermentation, gut bacteria metabolize various substrates (principally dietary components) to end products such as short-chain fatty acids and gases. This anaerobic metabolism is thought to contribute positively toward host daily energy requirements. However, under certain circumstances, the fermentative process may produce undesirable metabolites. This may cause the onset of gut disorders that can be manifest through both acute and chronic conditions. Moreover, the gut flora may become contaminated by transient pathogens that serve further to upset the normal community structure. There has been a recent increase in the use of dietary components that help to maintain, or even improve, the gut microflora "balance." Probiotics are live microbial feed supplements added to appropriate food vehicles (usually fermented milks), whereas prebiotics are dietary carbohydrates that have a selective metabolism in the colon and serve to increase numbers of bacteria seen as desirable. Because of their purported health-promoting properties, lactic acid-producing bacteria, including bifidobacteria, are the usual target organisms. The market value and biological potential of both approaches are enormous. This article will summarize how efficacious types can be identified.

Assimilation of sea-ice concentration in a global climate model — physical and statistical aspects

We investigate the initialization of Northern-hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates significantly reduces assimilation error both in identical-twin experiments and when assimilating sea-ice observations, reducing the concentration error by a factor of four to six, and the thickness error by a factor of two. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that the strong dependence of thermodynamic ice growth on ice concentration necessitates an adjustment of mean ice thickness in the analysis update. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that proportional mean-thickness updates are superior to the other two methods considered and enable us to assimilate sea ice in a global climate model using simple Newtonian relaxation.

Assimilation of sea-ice concentration in a global climate model — physical and statistical aspects

We investigate the initialisation of Northern Hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates leads to good assimilation performance for sea-ice concentration and thickness, both in identical-twin experiments and when assimilating sea-ice observations. The simulation of other Arctic surface fields in the coupled model is, however, not significantly improved by the assimilation. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that an adjustment of mean ice thickness in the analysis update is essential to arrive at plausible state estimates. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that assimilation with proportional mean-thickness updates outperforms the other two methods considered. The method described here is very simple to implement, and gives results that are sufficiently good to be used for initialising sea ice in a global climate model for seasonal to decadal predictions.