67 resultados para Process analysis


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Neutron diffraction has been used to study in situ the nanocrystallization process of Fe73.5Cu1Nb3Si22.5-xBx (x = 5, 9, and 12) amorphous alloys. Nanocrystallization results in a decrease of both the silicon content and the grain size of the Fe(Si) phase with increasing value of x. By comparing the radial distribution function peak areas with those predicted for ideal bcc and DO3 structure, it can be concluded that the ordering in DO3 Fe(Si) crystals increases with the silicon content.

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This paper presents a historical examination of employment in old age in Spain, in order to characterize this labour segment and identify and analyse its specific problems. One of these problems is the life-cycle deskilling process, already shown for certain national cases. This study explores whether this hypothesis also holds in Spain. The perspective used is essentially quantitative, as our analysis is based on the age-profession tables in Spanish population censuses from 1900 to 1970.

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This paper analyzes the relationship between spatial density of economic activity and interregional differences in the productivity of industrial labour in Spain during the period 1860-1999. In the spirit of Ciccone and Hall (1996) and Ciccone (2002), we analyze the evolution of this relationship over the long term in Spain. Using data on the period 1860-1999 we show the existence of an agglomeration effect linking the density of economic activity with labour productivity in the industry. This effect was present since the beginning of the industrialization process in the middle of the 19th century but has been decreasing over time. The estimated elasticity of labour productivity with respect to employment density was close to 8% in the subperiod 1860-1900, reduces to a value of around 7% in the subperiod 1914-1930, to 4% in the subperiod 1965-1979 and becomes insignificant in the final subperiod 1985-1999. At the end of the period analyzed there is no evidence of the existence of net agglomeration effects in the industry. This result could be explained by an important increase in the congestion effects in large industrial metropolitan areas that would have compensated the centripetal or agglomeration forces at work. Furthermore, this result is also consistent with the evidence of a dispersion of industrial activity in Spain during the last decades.

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The process of free reserves in a non-life insurance portfolio as defined in the classical model of risk theory is modified by the introduction of dividend policies that set maximum levels for the accumulation of reserves. The first part of the work formulates the quantification of the dividend payments via the expectation of their current value under diferent hypotheses. The second part presents a solution based on a system of linear equations for discrete dividend payments in the case of a constant dividend barrier, illustrated by solving a specific case.

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This paper analyzes the relationship between spatial density of economic activity and interregional differences in the productivity of industrial labour in Spain during the period 1860-1999. In the spirit of Ciccone and Hall (1996) and Ciccone (2002), we analyze the evolution of this relationship over the long term in Spain. Using data on the period 1860-1999 we show the existence of an agglomeration effect linking the density of economic activity with labour productivity in the industry. This effect was present since the beginning of the industrialization process in the middle of the 19th century but has been decreasing over time. The estimated elasticity of labour productivity with respect to employment density was close to 8% in the subperiod 1860-1900, reduces to a value of around 7% in the subperiod 1914-1930, to 4% in the subperiod 1965-1979 and becomes insignificant in the final subperiod 1985-1999. At the end of the period analyzed there is no evidence of the existence of net agglomeration effects in the industry. This result could be explained by an important increase in the congestion effects in large industrial metropolitan areas that would have compensated the centripetal or agglomeration forces at work. Furthermore, this result is also consistent with the evidence of a dispersion of industrial activity in Spain during the last decades.

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Didactic knowledge about contents is constructed through an idiosyncratic synthesis between knowledge about the subject area, students' general pedagogical knowledge and the teacher's biography. This study aimed to understand the construction process and the sources of Pedagogical Content Knowledge, as well as to analyze its manifestations and variations in interactive teaching by teachers whom the students considered competent. Data collection involved teachers from an undergraduate nursing program in the South of Brazil, through non-participant observation and semistructured interviews. Data analysis was submitted to the constant comparison method. The results disclose the need for initial education to cover pedagogical aspects for nurses; to assume permanent education as fundamental in view of the complexity of contents and teaching; to use mentoring/monitoring and the value learning with experienced teachers with a view to the development of quality teaching.

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The prediction of rockfall travel distance below a rock cliff is an indispensable activity in rockfall susceptibility, hazard and risk assessment. Although the size of the detached rock mass may differ considerably at each specific rock cliff, small rockfall (<100 m3) is the most frequent process. Empirical models may provide us with suitable information for predicting the travel distance of small rockfalls over an extensive area at a medium scale (1:100 000¿1:25 000). "Solà d'Andorra la Vella" is a rocky slope located close to the town of Andorra la Vella, where the government has been documenting rockfalls since 1999. This documentation consists in mapping the release point and the individual fallen blocks immediately after the event. The documentation of historical rockfalls by morphological analysis, eye-witness accounts and historical images serve to increase available information. In total, data from twenty small rockfalls have been gathered which reveal an amount of a hundred individual fallen rock blocks. The data acquired has been used to check the reliability of the main empirical models widely adopted (reach and shadow angle models) and to analyse the influence of parameters which affecting the travel distance (rockfall size, height of fall along the rock cliff and volume of the individual fallen rock block). For predicting travel distances in maps with medium scales, a method has been proposed based on the "reach probability" concept. The accuracy of results has been tested from the line entailing the farthest fallen boulders which represents the maximum travel distance of past rockfalls. The paper concludes with a discussion of the application of both empirical models to other study areas.

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This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations.

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This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations. Keywords: innovation sources; productivity; R&D Cooperation

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Composts are the products obtained after the aerobic degradation of different types of organic matter waste and can be used as substrates or substrate/soil amendments for plant cultivation. There is a small but increasing number of reports that suggest that foliar diseases may be reduced when using compost, rather than standard substrates, as growing medium. The purpose of this study was to examine the gene expression alteration produced by the compost to gain knowledge of the mechanisms involved in compost-induced systemic resistance. A compost from olive marc and olive tree leaves was able to induce resistance against Botrytis cinerea in Arabidopsis, unlike the standard substrate, perlite. Microarray analyses revealed that 178 genes were differently expressed, with a fold change cut-off of 1, of which 155 were up-regulated and 23 were down-regulated in compost-grown, as against perlite-grown plants. A functional enrichment study of up-regulated genes revealed that 38 Gene Ontology terms were significantly enriched. Response to stress, biotic stimulus, other organism, bacterium, fungus, chemical and abiotic stimulus, SA and ABA stimulus, oxidative stress, water, temperature and cold were significantly enriched, as were immune and defense responses, systemic acquired resistance, secondary metabolic process and oxireductase activity. Interestingly, PR1 expression, which was equally enhanced by growing the plants in compost and by B. cinerea inoculation, was further boosted in compost-grown pathogen-inoculated plants. Compost triggered a plant response that shares similarities with both systemic acquired resistance and ABA-dependent/independent abiotic stress responses.

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In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

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Background: Ethical conflicts are arising as a result of the growing complexity of clinical care, coupled with technological advances. Most studies that have developed instruments for measuring ethical conflict base their measures on the variables"frequency" and"degree of conflict". In our view, however, these variables are insufficient for explaining the root of ethical conflicts. Consequently, the present study formulates a conceptual model that also includes the variable"exposure to conflict", as well as considering six"types of ethical conflict". An instrument was then designed to measure the ethical conflicts experienced by nurses who work with critical care patients. The paper describes the development process and validation of this instrument, the Ethical Conflict in Nursing Questionnaire Critical Care Version (ECNQ-CCV). Methods: The sample comprised 205 nursing professionals from the critical care units of two hospitals in Barcelona (Spain). The ECNQ-CCV presents 19 nursing scenarios with the potential to produce ethical conflict in the critical care setting. Exposure to ethical conflict was assessed by means of the Index of Exposure to Ethical Conflict (IEEC), a specific index developed to provide a reference value for each respondent by combining the intensity and frequency of occurrence of each scenario featured in the ECNQ-CCV. Following content validity, construct validity was assessed by means of Exploratory Factor Analysis (EFA), while Cronbach"s alpha was used to evaluate the instrument"s reliability. All analyses were performed using the statistical software PASW v19. Results: Cronbach"s alpha for the ECNQ-CCV as a whole was 0.882, which is higher than the values reported for certain other related instruments. The EFA suggested a unidimensional structure, with one component accounting for 33.41% of the explained variance. Conclusions: The ECNQ-CCV is shown to a valid and reliable instrument for use in critical care units. Its structure is such that the four variables on which our model of ethical conflict is based may be studied separately or in combination. The critical care nurses in this sample present moderate levels of exposure to ethical conflict. This study represents the first evaluation of the ECNQ-CCV.

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Background: Ethical conflicts are arising as a result of the growing complexity of clinical care, coupled with technological advances. Most studies that have developed instruments for measuring ethical conflict base their measures on the variables"frequency" and"degree of conflict". In our view, however, these variables are insufficient for explaining the root of ethical conflicts. Consequently, the present study formulates a conceptual model that also includes the variable"exposure to conflict", as well as considering six"types of ethical conflict". An instrument was then designed to measure the ethical conflicts experienced by nurses who work with critical care patients. The paper describes the development process and validation of this instrument, the Ethical Conflict in Nursing Questionnaire Critical Care Version (ECNQ-CCV). Methods: The sample comprised 205 nursing professionals from the critical care units of two hospitals in Barcelona (Spain). The ECNQ-CCV presents 19 nursing scenarios with the potential to produce ethical conflict in the critical care setting. Exposure to ethical conflict was assessed by means of the Index of Exposure to Ethical Conflict (IEEC), a specific index developed to provide a reference value for each respondent by combining the intensity and frequency of occurrence of each scenario featured in the ECNQ-CCV. Following content validity, construct validity was assessed by means of Exploratory Factor Analysis (EFA), while Cronbach"s alpha was used to evaluate the instrument"s reliability. All analyses were performed using the statistical software PASW v19. Results: Cronbach"s alpha for the ECNQ-CCV as a whole was 0.882, which is higher than the values reported for certain other related instruments. The EFA suggested a unidimensional structure, with one component accounting for 33.41% of the explained variance. Conclusions: The ECNQ-CCV is shown to a valid and reliable instrument for use in critical care units. Its structure is such that the four variables on which our model of ethical conflict is based may be studied separately or in combination. The critical care nurses in this sample present moderate levels of exposure to ethical conflict. This study represents the first evaluation of the ECNQ-CCV.

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The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

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Life cycle analysis (LCA) is a comprehensive method for assessing the environmental impact of a product or an activity over its entire life cycle. The purpose of conducting LCA studies varies from one application to another. Different applications use LCA for different purposes. In general, the main aim of using LCA is to reduce the environmental impact of products through guiding the decision making process towards more sustainable solutions. The most critical phase in an LCA study is the Life Cycle Impact Assessment (LCIA) where the life cycle inventory (LCI) results of the considered substances related to the study of a certain system are transformed into understandable impact categories that represent the impact on the environment. In this research work, a general structure clarifying the steps that shall be followed ir order to conduct an LCA study effectively is presented. These steps are based on the ISO 14040 standard framework. In addition, a survey is done on the most widely used LCIA methodologies. Recommendations about possible developments and suggetions for further research work regarding the use of LCA and LCIA methodologies are discussed as well.