10 resultados para Perception of Aggression Scale (POAS)


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Corporate social responsibility (CSR) literature has largely neglected consumers’ perceptions in the debate regarding the role of CSR in the aftermath of the financial crisis. In that context, this study aims to test the possibility that consumers’ perceptions of CSR level, firm reputation and brand trust, might depend on the type of industry sector of a firm, the level of fit of an initiative or both. By conducting a survey on Portuguese consumers and running a two-way analysis of variance, it suggests that solely the type of industry sector has an effect on consumer perception and that consumers are less tolerable of controversial industries.

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The aim of this research is to evaluate if a premium beauty brand, in this case, Lancôme, can influence positively the purchase intention from Brazilian young adults, between 18 and 29 years old, consumers of beauty products, by initiating a relationship with a local celebrity or “it” girl on social media. This hypothesis has not been tested, and this research is a first attempt of evaluating it. Additionally, the consumer behavior, brand preferences and social media activeness of this age segment in Brazil are further studied as important insights for beauty brands to conquer these consumers. Results did not confirm the positive influence of local celebrities on this age segment’s purchase intention but several suggestions are made for future research to revisit this topic. Furthermore, there is a significant brand love for M.A.C., an international Lancôme competitor, amongst this target, as well as a probable price sensitivity facing premium beauty brands.

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This study aimed to understand employees’ reactions to organizational politics in Contact Centers. Drawing from a sample of 187 supervisor-employee dyads, we studied the relationship between employees’ perceptions of organizational politics and supervisor-rated task performance and deviance, and mediation effects by authenticity at work and affective commitment. Results indicate that workers tend to react to workplace politics with deviant behavior and worse task performance. We found that the relationship between perceived politics and task performance was mediated by authenticity. The relationship between perceived politics and supervisor-rated deviance was mediated by affective commitment to the organization. Implications for management are discussed.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

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A thesis submitted in fulfilment of the requirements for the Degree of Doctor of Philosophy in Sanitary Engineering in the Faculty of Sciences and Technology of the New University of Lisbon

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RESUMO: Um dos principais resultados das intervenções de Fisioterapia dirigidas a utentes com Dor Lombar Crónica (DLC) é reduzir a incapacidade funcional. A Quebec Back Pain Disability Scale (QBPDS) é um instrumento amplamente aceite a nível internacional na medição do nível de incapacidade funcional reportada pelos indivíduos com DLC. O objetivo deste estudo é dar um contributo para a adaptação cultural da versão portuguesa da QBPDS (QBPDS-VP) e investigar o poder de resposta e interpretabilidade da escala. Metodologia: Realizou-se um estudo metodológico, multicentro, baseado num coorte prospetivo de 132 utentes com DLC. Os utentes foram recrutados a partir da lista de espera de 16 serviços de Medicina Física e de Reabilitação/Fisioterapia de várias áreas geográficas de Portugal. A QBPDS- VP foi administrada 3 vezes, em 3 momentos de recolha de dados distintos: T0 - momento inicial (utentes em lista de espera); T1 - 1 semana de intervalo (início dos tratamentos de Fisioterapia); e T2 - 6 semanas de intervalo (pós-intervenção de Fisioterapia). Os dados recolhidos em T0 foram utilizados para a análise fatorial e para o estudo da consistência interna (n=132); os dados da amostra emparelhada de T0 e T1 (n=132) para a fiabilidade teste-reteste; e os dados da amostra emparelhada de T0 e T2 (n=120) para a análise do poder de resposta e interpretabilidade. A âncora externa utilizada foi a perceção global de mudança, neste caso a PGIC- VP, que foi respondida em T1 e T2. O nível de significância para o qual os valores se consideraram satisfatórios foi de p≤ 0,05. O tratamento dos dados foi realizado no software IBM SPSS Statistics (versão 20). Resultados: A QBPDS- VP é uma escala unidimensional, que revela uma excelente consistência interna (α de Cronbach= 0,95) e uma fiabilidade teste-reteste satisfatória (CCI= 0,696; IC 95%: 0,581–0,783). Esta escala demonstrou um poder de resposta moderado, quando aplicada em utentes com DLC ( = 0,426 e AAC= 0,741; IC 95%: 0,645 – 0,837). A Diferença Mínima Detetável (DMD) estimada foi de 19 pontos e as estimativas da Diferença Mínima Clinicamente Importante (DMCI) variaram entre 7 (pelo método curva ROC) e 8 pontos (pelo método “diferença média de pontuação”). A estimativa pela curva ROC deriva do ponto ótimo de corte de 6,5 pontos, com Área Abaixo da Curva (AAC)= 0,741, sensibilidade de 72%, e especificidade de 71%. Uma análise complementar da curva ROC baseada nas diferenças de pontuações da QBPDS, expressa em percentagem, revelou um ponto ótimo de corte de - 24% (AAC= 0,737, sensibilidade de 71%, e especificidade de 71%). Para pontuações iniciais da QBPDS- VP mais altas (≥34 pontos), foi encontrado um ponto ótimo de corte de 10,5 pontos (AAC= 0,738, sensibilidade de 73%, e especificidade de 67%). Conclusão: A QBPDS-VP demonstrou bons níveis de fiabilidade e poder de resposta, recomendando-se o seu uso na medição e avaliação da incapacidade funcional de utentes com DLC. A DMD estimada, de 19 pontos, determinou uma amplitude válida da QBPDS-VP de 19 a 81 pontos. Este estudo propõe estimativas de DMCI da QBPDS- VP numa aplicação específica da escala (em utentes com DLC que são referidos para a intervenção de Fisioterapia). A pontuação inicial da QBPDS- VP deve ser considerada na interpretação de mudanças de pontuação, após a intervenção de Fisioterapia.------------ ABSTRACT: One of the main results of physiotherapy interventions for patients with Chronic Low Back Pain (CLBP) is decrease the functional disability. The Quebec Back Pain Disability Scale (QBPDS) is an instrument widely accepted internationally, in measuring the level of disability reported by individuals with CLBP. The purpose of this study is to contribute to the cultural adaptation of the Portuguese version of QBPDS (QBPDS - PV) and investigate the Responsiveness and Interpretability of QBPDS-PV. Methodology: This was a methodological and multicenter study, based on a sample of 132 subjects with CLBP. The patients were recruited from the waiting lists of 16 medicine rehabilitation service, in many Portugal districts. The Quebec Back Pain Disability Scale was administered in three different moments: T0 – baseline (patients in the waiting list); T1- one week after T0 (the beginning of treatment); and T2 – six weeks after T1 (the posttreatment). The data collected at T0 were used for factor analysis and to study the internal consistency (n = 132); paired sample data of T0 and T1 (n=132) were used for test-retest reliability, and sample data paired for T0 and T2 (n=120) used for responsiveness and interpretability analysis. The external anchor was the global perception of change, measured by the Portuguese version of Patient’s Global Impression of Change (PGIC) Scale. The minimal level of significance established was p ≤ 0,05. Data analysis was performed using the IBM SPSS Statistics software (version 20). Results: The QBPDS-PV is a unidimensional scale, demonstrates an excellent internal consistency (Cronbach's α=0.95) and satisfactory test-retest reliability (ICC= 0.696, 95% CI: 0.581–0.783). The scale revealed moderate responsiveness when applied to patients with CLBP ( = 0.426 and AUC= 0.741, 95% CI: 0.645 - 0.837). The Smallest Detectable Change (SDC) was 19 points, whereas the Minimal Clinically Important Change (MCIC) ranged between 7 (ROC curve method) and 8 points (by the "mean difference score"). The estimate was derived from the ROC curve by an optimal cutoff point of 6.5 points, with Area Under the Curve (AUC)= 0.741, sensitivity 72%, and specificity of 71%. A complementary analysis of the ROC curve based on differences in QBPDS scores from baseline, expressed in percentage, revealed an optimal cutoff point of -24% (AUC= 0.737, sensitivity of 71%, and specificity of 71%). For the highest initial scores of QBPDS-PV (≥ 34 points) was found an optimal cutoff of 10.5 points (AUC= 0.738, sensitivity of 73%, and specificity 67%). Conclusion: The QBPDS-PV demonstrated good levels of reliability and responsiveness, being recommended its use in the measurement and evaluation of disability of patients with CLBP. The SDC of 19 points determined the QBPDS‟ scale width of 19 to 81. This study proposes MCIC values for QBPDS –PV for this specific setting (in CLBP patients who are referred for physiotherapy intervention). The QBPDS –PV baseline score have to be taken into account while interpreting the score change after physiotherapy intervention.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica