À procura da identidade de Heinz : um modelo de compreensão da motivação moral

RESUMO: As teorias psicológicas da moralidade dividem-se na conceptualização da motivação moral, o tema desta dissertação. Os modelos construtivistas, apoiados na epistemologia genética, privilegiam a cognição como factor determinante mas, as teorias que enfatizam o funcionamento individual admitem que as emoções e a identidade interferem na tendência de cada pessoa agir moralmente. Particularmente apoiados na segunda perspectiva, testámos um modelo preditor da motivação moral com três variáveis, identidade, identidade moral e integridade, todas avaliadas por medidas psicométricas, em duas amostras. A primeira era composta por 320 estudantes do 12º ano de uma escola do concelho de Lisboa, com idades compreendidas entre 18 e 20 anos (M=18,22; Dp=0,49), 108 masculinos e 194 femininos e a segunda era composta por 174 sujeitos, estudantes finalistas de cursos profissionais de uma escola do concelho de Lisboa frequentada por alunos provenientes de ambientes sociais caracterizados pelo stresse sócio-económico e familiar, e até, em bastantes casos, que já tinham participado em actos ilegais relacionados com furto, vandalismo, tráfico de drogas, e agressões, com idades compreendidas entre 18 e 22 anos (M=18,98; Dp=1,075), 104 masculinos e 70 femininos. A primeira amostra foi considerada normativa e a segunda de risco psicossocial. Para avaliar a motivação moral foi construída uma medida que incluiu dois aspectos: a consciência moral, relativa à avaliação objectiva e subjectiva que os indivíduos fazem das situações morais que através de processos de análise de conteúdo foi distinguida em três categorias exclusivas: não transgressão, transgressão relativizada e transgressão; e a autoatribuição de emoções que indica a probabilidade objectiva dos indivíduos cometerem acções morais. Foi verificada a existência de diferenças individuais em ambas as medidas da motivação moral e, também, a existência de diferenças na atribuição de emoções em função da consciência moral: os sujeitos da categoria transgressão apresentaram atribuições mais negativas do que os sujeitos de transgressão relativizada e estes, por sua vez, apresentaram atribuições mais negativas que os sujeitos da categoria não transgressão. Estes resultados confirmam o papel da identidade na motivação moral. A análise da predição confirmou que a integridade, a identidade e a identidade moral, em ordem decrescente de capacidade explicativa, constituem factores preditores tanto da consciência moral como da auto-atribuição de emoções. ABSTRACT: Moral motivation, the subject of this thesis, is differently viewed by several psychological perspectives. Constructivist models supported by genetic epistemology define cognition as the determinant factor while theories that emphasize individual functioning admit that emotions and identity have a central role in the way that persons could morally act. Particularly supported in this second approach we tested a predictive model of moral motivation with three variables, identity, moral identity and integrity, all evaluated by psychometric scales, in two samples. The first sample had 320 graduate high school students with age between 18 and 20 (M=18,22; SD=0,49), 108 male and 194 female and the second sample had 174 graduate students of vocational courses in high school of a risk social and familiar environment, many of them had already done illegal acts such as stealing, vandalism, drug traffic and aggressions; they had ages between 18 and 22 (M=18,98; SD=1,08), 104 male and 70 female. The first sample was considered normative and the second one was classified as psychosocial risk. To evaluate moral motivation we developed a measure that assesses two aspects: moral conscience, who includes both objective and subjective evaluation of moral situations that was distinguished in three exclusive categories by procedures of content analysis: non-transgression, justifiable transgression and transgression; and self-attribution of emotion that indicates the likelihood of committing moral actions. We observed individual differences in both measurements of moral motivation and also verified differences in emotional attribution on the basis of moral conscience: the individuals of transgression category presented more negative attributions than those of justifiable transgression and in turn the latter presented more negative attributions than individuals of non-transgression category. These results confirm the role of identity in moral motivation. The predictor analysis confirmed integrity, identity and moral identity, in descending order of explanatory power, as predictive variables of moral consciousness and self-attribution of emotions.

Modelling trade contractor information production

Design management research usually deals with the processes within the professional design team and yet, in the UK, the volume of the total project information produced by the specialist trade contractors equals or exceeds that produced by the design team. There is a need to understand the scale of this production task and to plan and manage it accordingly. The model of the process on which the plan is to be based, while generic, must be sufficiently robust to cover the majority of instances. An approach using design elements, in sufficient depth to possibly develop tools for a predictive model of the process, is described. The starting point is that each construction element and its components have a generic sequence of design activities. Specific requirements tailor the element's application to the building. Then there are the constraints produced due to the interaction with other elements. Therefore, the selection of a component within the element may impose a set of constraints that will affect the choice of other design elements. Thus, a design decision can be seen as an interrelated element-constraint-element (ECE) sub-net. To illustrate this approach, an example of the process within precast concrete cladding has been used.

Modelling trade contractor information production

Design management research usually deals with the processes within the professional design team and yet, in the UK, the volume of the total project information produced by the specialist trade contractors equals or exceeds that produced by the design team. There is a need to understand the scale of this production task and to plan and manage it accordingly. The model of the process on which the plan is to be based, while generic, must be sufficiently robust to cover the majority of instances. An approach using design elements, in sufficient depth to possibly develop tools for a predictive model of the process, is described. The starting point is that each construction element and its components have a generic sequence of design activities. Specific requirements tailor the element's application to the building. Then there are the constraints produced due to the interaction with other elements. Therefore, the selection of a component within the element may impose a set of constraints that will affect the choice of other design elements. Thus, a design decision can be seen as an interrelated element-constraint-element (ECE) sub-net. To illustrate this approach, an example of the process within precast concrete cladding has been used.

UK construction orders and output: A comparison of government and commercially available data 1995-2001

Because of the importance and potential usefulness of construction market statistics to firms and government, consistency between different sources of data is examined with a view to building a predictive model of construction output using construction data alone. However, a comparison of Department of Trade and Industry (DTI) and Office for National Statistics (ONS) series shows that the correlation coefcient (used as a measure of consistency) of the DTI output and DTI orders data and the correlation coefficient of the DTI output and ONS output data are low. It is not possible to derive a predictive model of DTI output based on DTI orders data alone. The question arises whether or not an alternative independent source of data may be used to predict DTI output data. Independent data produced by Emap Glenigan (EG), based on planning applications, potentially offers such a source of information. The EG data records the value of planning applications and their planned start and finish dates. However, as this data is ex ante and is not correlated with DTI output it is not possible to use this data to describe the volume of actual construction output. Nor is it possible to use the EG planning data to predict DTI construc-tion orders data. Further consideration of the issues raised reveal that it is not practically possible to develop a consistent predictive model of construction output using construction statistics gathered at different stages in the development process.

Predicting space climate change

The recent decline in the open magnetic flux of the Sun heralds the end of the Grand Solar Maximum (GSM) that has persisted throughout the space age, during which the largest‐fluence Solar Energetic Particle (SEP) events have been rare and Galactic Cosmic Ray (GCR) fluxes have been relatively low. In the absence of a predictive model of the solar dynamo, we here make analogue forecasts by studying past variations of solar activity in order to evaluate how long‐term change in space climate may influence the hazardous energetic particle environment of the Earth in the future. We predict the probable future variations in GCR flux, near‐Earth interplanetary magnetic field (IMF), sunspot number, and the probability of large SEP events, all deduced from cosmogenic isotope abundance changes following 24 GSMs in a 9300‐year record.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Fine root isotropy in Eucalyptus grandis plantations. Towards the prediction of root length densities from root counts on trench walls

The objectives of the study were to assess changes in fine root anisotropy and specific root lengths throughout the development of Eucalyptus grandis ( W. Hill ex Maiden) plantations and to establish a predictive model of root length density (RLD) from root intercept counts on trench walls. Fine root densities (<1 mm in diameter) were studied in 6-, 12-, 22-, 28-, 54-, 68- and 72-month-old E. grandis plantations established on deep Ferralsols in southern Brazil. Fine root intercepts were counted on 3 faces of 90-198 soil cubes (1 dm(3) in volume) in each stand and fine root lengths (L) were measured inside 576 soil cubes, sampled between the depths of 10 cm and 290 cm. The number of fine root intercepts was counted on one vertical face perpendicular to the planting row (N(t)), one vertical face parallel to the planting row (N(l)) and one horizontal face (N(h)), for each soil cube sampled. An overall isotropy of fine roots was shown by paired Student's t-tests between the numbers of fine roots intersecting each face of soil cubes at most stand ages and soil depths. Specific root lengths decreased with stand age in the upper soil layers and tended to increase in deep soil layers at the end of the rotation. A linear regression established between N(t) and L for all the soil cubes sampled accounted for 36% of the variability of L. Such a regression computed for mean Nt and L values at each sampling depth and stand age explained only 55% of the variability, as a result of large differences in the relationship between L and Nt depending on stand productivity. The equation RLD=1.89*LAI*N(t), where LAI was the stand leaf area index (m(2) m(-2)) and Nt was expressed as the number of root intercepts per cm(2), made it possible to predict accurately (R(2)=0.84) and without bias the mean RLDs (cm cm(-3)) per depth in each stand, for the whole data set of 576 soil cubes sampled between 2 years of age and the end of the rotation.

Desidratação de polpas de frutas pelo método foam-mat

This study aimed to investigate the foam mat drying process of pineapple and mango pulp, as well as to evaluate the final product quality. Initially, the selection of fruit and additives was conducted based on density and stability determinations of mango, seriguela, umbu and pineapple foams. After selecting pineapple and mango for further studies, the fruit pulps and fruit foams were characterized in regard to their physicochemical composition. The temperature (60oC or 70oC) and the foam thickness (4 and 11 mm) were evaluated in accordance to the obtained drying curves and after model adjustment. Mango and pineapple powders obtained at the best process conditions were characterized in regard to their physicochemical composition, solubility, reconstitution time. Yoghurts were prepared with the addition of pineapple and mango powders and they were evaluated for their sensory acceptance. Results show that the best drying rates were achieved by using 70o C and layers 4mm thick for both fruits. The Page model successfully fitted the drying experimental data and it can be used as a predictive model. Pineapple and mango powders showed acid pH, high soluble solids content, low water activity (approx. 0.25), lipids between 1.46% and 2.03%, protein around 2.00%, and ascorbic acid content of 17,73 mg/100g and 14.32 mg/100g, for mango and pineapple, respectively. It was observed higher ascorbic acid retention for pineapple and mango powders processed at 70o C, which would be explained by the lower drying time applied. The fruit powders exhibited high solubility and fast reconstitution in water. The sensory acceptance indexes for yoghurts with the addition of both fruit powders were higher than 70%, which reflect the satisfactory product acceptance

Estudo do equilíbrio líquido-vapor do sistema água+etanol+líquido iônico visando a separação do álcool anidro

Anhydrous ethanol is used in chemical, pharmaceutical and fuel industries. However, current processes for obtaining it involve high cost, high energy demand and use of toxic and pollutant solvents. This problem occurs due to the formation of an azeotropic mixture of ethanol + water, which does not allow the complete separation by conventional methods such as simple distillation. As an alternative to currently used processes, this study proposes the use of ionic liquids as solvents in extractive distillation. These are organic salts which are liquids at low temperatures (under 373,15 K). They exhibit characteristics such as low volatility (almost zero/ low vapor ), thermal stability and low corrosiveness, which make them interesting for applications such as catalysts and as entrainers. In this work, experimental data for the vapor pressure of pure ethanol and water in the pressure range of 20 to 101 kPa were obtained as well as for vapor-liquid equilibrium (VLE) of the system ethanol + water at atmospheric pressure; and equilibrium data of ethanol + water + 2-HDEAA (2- hydroxydiethanolamine acetate) at strategic points in the diagram. The device used for these experiments was the Fischer ebulliometer, together with density measurements to determine phase compositions. The experimental data were consistent with literature data and presented thermodynamic consistency, thus the methodology was properly validated. The results were favorable, with the increase of ethanol concentration in the vapor phase, but the increase was not shown to be pronounced. The predictive model COSMO-SAC (COnductor-like Screening MOdels Segment Activity Coefficient) proposed by Lin & Sandler (2002) was studied for calculations to predict vapor-liquid equilibrium of systems ethanol + water + ionic liquids at atmospheric pressure. This is an alternative for predicting phase equilibrium, especially for substances of recent interest, such as ionic liquids. This is so because no experimental data nor any parameters of functional groups (as in the UNIFAC method) are needed

Síndrome da fragilidade e fatores associados em idosos comunitários do município de Santa Cruz RN

The frailty in the elderly is characterized by decreased physiological reserves, and is associated with increased risk of disability and high vulnerability to morbidity and mortality. This study is part of a multicentric project on Frailty in Elderly Brazilians (REDE FIBRA). Aims: to investigate characteristics, prevalence and associated factors related to frailty. Metodology: We interviewed 391 elderly patients aged 65 years, selected randomly. Data collection was performed using a multidimensional questionnaire containing information about socio-demographic and clinical variables. To characterize the frail elderly, was considered the phenotype proposed by Fried. Data were analyzed using descriptive statistics, bivariate analysis (χ ²) and binary logistic regression. Results: The prevalence of frailty was 17.1%. In the final model of multivariate analysis, was obtained as factors associated with frailty: advanced chronological age (p <0.001), have comorbidity (p <0.035), show dependence on performing basic activities of daily living (p <0.010) and instrumental (p <0.003) and have poor perception of health status (p <0030). Conclusions: The factors associated with frailty suggest a predictive model helping to understand the syndrome, guiding actions that minimize adverse effects on the aging process

The Incremental Shuttle Walk Test in Older Brazilian Adults

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Caracterização da cobertura vegetal na equação universal de perda de solos (fator C) por meio de geotecnologias

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Caracterização da erosão hídrica laminar do solo em bacia hidrográfica com base na malha fundiária, por meio de sensoriamento remoto, geoprocessamento e modelagem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimando o desfecho no recém-nascido grave através da Lógica Fuzzy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)