53 resultados para case-based reasoning


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In this paper we identify the requirements for creating formal descriptions of learning scenarios designed under the European HigherEducation Area paradigm, using competences and learning activities as the basic pieces of the learning process, instead of contents and learning resources, pursuing personalization. Classical arrangements of content based courses are no longer enough to describe all the richness of this new learning process, where user profiles, competences and complex hierarchical itineraries need to be properly combined. We study the intersection with the current IMS Learning Design specification and theadditional metadata required for describing such learning scenarios. This new approach involves the use of case based learning and collaborativelearning in order to acquire and develop competences, following adaptive learning paths in two structured levels.

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Objective: To understand nursing student's self-consciousness and his/her autonomy in the discipline of fundamentals of professional care in the context of a liberating pedagogical proposal. Methodology. This qualitative, case-based research in the model of Ludke and André involved 14 students participating in the discipline. Data were collected by non-participatory observation and analysis of documents. Field observation was conducted from March to July 2010 and data were collected according to the proposal of Minayo: pre-analysis, exploration of material and treatment of results. Results. We constructed two thematic units of analysis: from "being to the self" and exercise of "become to be". Conclusion. When nursing students feel more liberty, they have the opportunity to substitute the scary prospect of learning something new material to something that motivates their curiosity and leads them to become more autonomous.

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The public perception of the EU in Spain varies greatly. The most positive aspects of Spanish membership are associated with the consolidation of democracy, economic growth, the introduction of the euro, the growth in employment and structural and cohesion funds, the increase in the female participation rate, and the equal opportunities policies. The analysts are in favour of common objectives in the employment policy and multi-level government. The less positive aspects of the EU are the risks of losing social protection and loss of employment in some sectors due to mergers of multinationals and delocalization of companies towards Eastern Europe. The continuous demands for reform of the welfare state, the toughening of the conditions of access to social benefit and the reform of the labour market are also seen as problematic issues. Risks of competitive cuts and social dumping.

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Report for the scientific sojourn carried out at the Model-based Systems and Qualitative Reasoning Group (Technical University of Munich), from September until December 2005. Constructed wetlands (CWs), or modified natural wetlands, are used all over the world as wastewater treatment systems for small communities because they can provide high treatment efficiency with low energy consumption and low construction, operation and maintenance costs. Their treatment process is very complex because it includes physical, chemical and biological mechanisms like microorganism oxidation, microorganism reduction, filtration, sedimentation and chemical precipitation. Besides, these processes can be influenced by different factors. In order to guarantee the performance of CWs, an operation and maintenance program must be defined for each Wastewater Treatment Plant (WWTP). The main objective of this project is to provide a computer support to the definition of the most appropriate operation and maintenance protocols to guarantee the correct performance of CWs. To reach them, the definition of models which represent the knowledge about CW has been proposed: components involved in the sanitation process, relation among these units and processes to remove pollutants. Horizontal Subsurface Flow CWs are chosen as a case study and the filtration process is selected as first modelling-process application. However, the goal is to represent the process knowledge in such a way that it can be reused for other types of WWTP.

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Export activities are a major source of economic growth and are considered important both at the national level and for individual businesses. Moreover, in the case of SMEs, they gain particular relevance, exporting being the most common foreign market entry mode for these firms. The decision maker’s role in the export activity is crucial, particularly in the case of SMEs. However, the extant literature on internationalization is characterized by a lack of consensus among scholars as to what constitutes the managerial factor in determining exporting. Therefore, this study focuses on the following issue: Which are the decision maker’s characteristics and perceptions that may influence the export behaviour of Catalan SMEs? To address this question a multiple case study method is applied across four Catalan exporting SMEs. The methodology chosen for analysing the empirical data is relying on the proposition testing approach while the investigation is conducted including both within and cross-case analysis. The findings show that high educational level, language skills, high risk tolerance, innovativeness as well as strongly perceived export stimuli as compared to low and easy to overcome export barriers positively influence the export involvement and development of SMEs. The study provides further insights into the research topic by jointly studying managerial characteristics and perceptions. Additionally, the majority of research on exporting topics has been carried out in the USA, so there is a clear need of investigation in the field in other countries, moreover in Spain where the exporting activities have not been as widely studied.

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The main aim of this work is to define an environmental tax on products and services based on their carbon footprint. We examine the relevance of conventional life cycle analysis (LCA) and environmentally extended input-output analysis (EIO) as methodological tools to identify emission intensities of products and services on which the tax is based. The short-term price effects of the tax and the policy implications of considering non-GHG are also analyzed. The results from the specific case study on pulp production show that the environmental tax rate based on the LCA approach (1,8%) is higher than both EIO approaches (0,8% for product and 1,4% for industry approach), but they are comparable. Even though LCA is more product specific and provides detailed analysis, EIO would be the more relevant approach to apply economy wide environmental tax. When the environmental tax considers non-GHG emissions instead of only CO2, sectors such as agriculture, mining of coal and extraction of peat, and food exhibit higher environmental tax and price effects. Therefore, it is worthwhile for policy makers to pay attention on the implication of considering only CO2 tax or GHG emissions tax in order for such a policy measure to be effective and meaningful. Keywords: Environmental tax; Life cycle analysis; Environmental input-output analysis.

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Agent-based computational economics is becoming widely used in practice. This paperexplores the consistency of some of its standard techniques. We focus in particular on prevailingwholesale electricity trading simulation methods. We include different supply and demandrepresentations and propose the Experience-Weighted Attractions method to include severalbehavioural algorithms. We compare the results across assumptions and to economic theorypredictions. The match is good under best-response and reinforcement learning but not underfictitious play. The simulations perform well under flat and upward-slopping supply bidding,and also for plausible demand elasticity assumptions. Learning is influenced by the number ofbids per plant and the initial conditions. The overall conclusion is that agent-based simulationassumptions are far from innocuous. We link their performance to underlying features, andidentify those that are better suited to model wholesale electricity markets.

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In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows) in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS) environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM) with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.

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Background: Protein domains represent the basic units in the evolution of proteins. Domain duplication and shuffling by recombination and fusion, followed by divergence are the most common mechanisms in this process. Such domain fusion and recombination events are predicted to occur only once for a given multidomain architecture. However, other scenarios may be relevant in the evolution of specific proteins, such as convergent evolution of multidomain architectures. With this in mind, we study glutaredoxin (GRX) domains, because these domains of approximately one hundred amino acids are widespread in archaea, bacteria and eukaryotes and participate in fusion proteins. GRXs are responsible for the reduction of protein disulfides or glutathione-protein mixed disulfides and are involved in cellular redox regulation, although their specific roles and targets are often unclear. Results: In this work we analyze the distribution and evolution of GRX proteins in archaea,bacteria and eukaryotes. We study over one thousand GRX proteins, each containing at least one GRX domain, from hundreds of different organisms and trace the origin and evolution of the GRX domain within the tree of life. Conclusion: Our results suggest that single domain GRX proteins of the CGFS and CPYC classes have, each, evolved through duplication and divergence from one initial gene that was present in the last common ancestor of all organisms. Remarkably, we identify a case of convergent evolution in domain architecture that involves the GRX domain. Two independent recombination events of a TRX domain to a GRX domain are likely to have occurred, which is an exception to the dominant mechanism of domain architecture evolution.

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The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.

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In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications.

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A theory of network-entrepreneurs or "spin-off system" is presented in this paper for the creation of firms based on the community’s social governance. It is argued that firm’s capacity for accumulation depends on the presence of employees belonging to the same social/ethnic group with expectations of "inheriting" the firm and becoming entrepreneurs once they have been selected for their merits and loyalty towards their patrons. Such accumulation is possible because of the credibility of the patrons’ promises of supporting newcomers due to high social cohesion and specific social norms prevailing in the community. This theory is exemplified through the case of the Barcelonnettes, a group of immigrants from the Alps in the South of France (Provence) who came to Mexico in the XIX Century.

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The paper presents a foundation model for Marxian theories of the breakdown of capitalism based on a new falling rate of profit mechanism. All of these theories are based on one or more of "the historical tendencies": a rising capital-wage bill ratio, a rising capitalist share and a falling rate of profit. The model is a foundation in the sense that it generates these tendencies in the context of a model with a constant subsistence wage. The newly discovered generating mechanism is based on neo-classical reasoning for a model with land. It is non-Ricardian in that land augmenting technical progress can be unboundedly rapid. Finally, since the model has no steady state, it is necessary to use a new technique, Chaplygin's method, to prove the result.

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The paper presents a foundation model for Marxian theories of the breakdown of capitalism based on a new falling rate of profit mechanism. All of these theories are based on one or more of ?the historical tendencies?: a rising capital-wage bill ratio, a rising capitalist share and a falling rate of profit. The model is a foundation in the sense that it generates these tendencies in the context of a model with a constant subsistence wage. The newly discovered generating mechanism is based on neo-classical reasoning for a model with land. It is non-Ricardian in that land augmenting technical progress can be unboundedly rapid. Finally, since the model has no steady state, it is necessary to use a new technique, Chaplygin?s method, to prove the result.

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In this paper we analyze the determination of "key" sectors in the final energy consumption. We approach this issue from an input-output perspective and we design a methodology based on the elasticities of the demands of final energy consumption. As an exercise, we apply the proposed methodology to the Spanish economy. The analysis allows us to indicate the greater or lesser relevance of the different sectors in the consumption of final energy, pointing out which sectors deserve greater attention in the Spanish case and showing the implications for energy policy.