6,935 research outputs found
The role of social interaction in farmers' climate adaptation choice
Adaptation to climate change might not always occur, with potentially\ud
catastrophic results. Success depends on coordinated actions at both\ud
governmental and individual levels (public and private adaptation). Even for a âwetâ country like the Netherlands, climate change projections show that the frequency and severity of droughts are likely to increase. Freshwater is an important factor for agricultural production. A deficit causes damage to crop production and consequently to a loss of income. Adaptation is the key to decrease farmersâ vulnerability at the micro level and the sectorâs vulnerability at the macro level. Individual adaptation decision-making is determined by the behavior of economic agents and social interaction among them. This can be best studied with agentbased modelling. Given the uncertainty about future weather conditions and the costs and effectiveness of adaptation strategies, a farmer in the model uses a cognitive process (or heuristic) to make adaptation decisions. In this process, he can rely on his experiences and on information from interactions within his social network. Interaction leads to the spread of information and knowledge that causes learning. Learning changes the conditions for individual adaptation decisionmaking. All these interactions cause emergent phenomena: the diffusion of adaptation strategies and a change of drought vulnerability of the agricultural sector. In this paper, we present a conceptual model and the first implementation of an agent-based model. The aim is to study the role of interaction in a farmerâs social network on adaptation decisions and on the diffusion of adaptation strategies\ud
and vulnerability of the agricultural sector. Micro-level survey data will be used to parameterize agentsâ behavioral and interaction rules at a later stage. This knowledge is necessary for the successful design of public adaptation strategies, since governmental adaptation actions need to be fine-tuned to private adaptation behavior
The dynamics of a low-order coupled ocean-atmosphere model
A system of five ordinary differential equations is studied which combines
the Lorenz-84 model for the atmosphere and a box model for the ocean. The
behaviour of this system is studied as a function of the coupling parameters.
For most parameter values, the dynamics of the atmosphere model is dominant.
For a range of parameter values, competing attractors exist. The Kaplan-Yorke
dimension and the correlation dimension of the chaotic attractor are
numerically calculated and compared to the values found in the uncoupled Lorenz
model. In the transition from periodic behaviour to chaos intermittency is
observed. The intermittent behaviour occurs near a Neimark-Sacker bifurcation
at which a periodic solution loses its stability. The length of the periodic
intervals is governed by the time scale of the ocean component. Thus, in this
regime the ocean model has a considerable influence on the dynamics of the
coupled system.Comment: 20 pages, 15 figures, uses AmsTex, Amssymb and epsfig package.
Submitted to the Journal of Nonlinear Scienc
Metabifurcation analysis of a mean field model of the cortex
Mean field models (MFMs) of cortical tissue incorporate salient features of
neural masses to model activity at the population level. One of the common
aspects of MFM descriptions is the presence of a high dimensional parameter
space capturing neurobiological attributes relevant to brain dynamics. We study
the physiological parameter space of a MFM of electrocortical activity and
discover robust correlations between physiological attributes of the model
cortex and its dynamical features. These correlations are revealed by the study
of bifurcation plots, which show that the model responses to changes in
inhibition belong to two families. After investigating and characterizing
these, we discuss their essential differences in terms of four important
aspects: power responses with respect to the modeled action of anesthetics,
reaction to exogenous stimuli, distribution of model parameters and oscillatory
repertoires when inhibition is enhanced. Furthermore, while the complexity of
sustained periodic orbits differs significantly between families, we are able
to show how metamorphoses between the families can be brought about by
exogenous stimuli. We unveil links between measurable physiological attributes
of the brain and dynamical patterns that are not accessible by linear methods.
They emerge when the parameter space is partitioned according to bifurcation
responses. This partitioning cannot be achieved by the investigation of only a
small number of parameter sets, but is the result of an automated bifurcation
analysis of a representative sample of 73,454 physiologically admissible sets.
Our approach generalizes straightforwardly and is well suited to probing the
dynamics of other models with large and complex parameter spaces
Development of motivation in first-year students in Dutch senior secondary vocational education
This study examined the development in motivation for school in students in senior secondary vocational education and factors related to this development. There have been many concerns about a decline in motivation after school transitions. Little about this subject is known in relation to the transition to senior secondary vocational education. Knowledge about this is necessary, as the decline is expected to be more extensive in this type of school because the percentage of dropouts is high. For this research, 614 first-year students filled out a questionnaire four times. The results showed little average change in motivation during the first school year, although there was a decrease in students' academic delay of gratification after the transition. Associations with motivation similar to those found in studies of secondary schools were found, but only at the start of the school year, not with changes in it during the remainder of the year
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