283 resultados para OLS
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Toluene dioxygenase (TDO)-catalysed benzylic hydroxylation of indene substrates (8, 16 and 17), using whole cell cultures of Pseudomonas putida UV4, was found to yield inden-1-ol (14 and 22) and indan-1-one bioproducts (15 and 23). The formation of these bioproducts is consistent with the involvement of carbon-centred radical intermediates. TDO-catalysed oxidation of indenes 8 and 16 also gave cis-diols 13 and 18 respectively. TDO and naphthalene dioxygenase (NDO), used as both whole-cell preparations and as purified enzymes, were found to catalyse the benzylic hydroxylation of chromane 30, deuteriated (+/-)-chromane 30(D) and enantiomers (4S)-30(D) and (4R)-30(D) to yield (4R)- and (4S)-chroman-4-ols 31/31(D) respectively. The mechanism of benzylic hydroxylation of chromane 30/30(D) involves the stereoselective abstraction of a pro-R (with TDO) or a pro-S (with NDO) hydrogen atom at C-4 and a marked preference for retention of configuration.
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It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.
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A number of neural networks can be formulated as the linear-in-the-parameters models. Training such networks can be transformed to a model selection problem where a compact model is selected from all the candidates using subset selection algorithms. Forward selection methods are popular fast subset selection approaches. However, they may only produce suboptimal models and can be trapped into a local minimum. More recently, a two-stage fast recursive algorithm (TSFRA) combining forward selection and backward model refinement has been proposed to improve the compactness and generalization performance of the model. This paper proposes unified two-stage orthogonal least squares methods instead of the fast recursive-based methods. In contrast to the TSFRA, this paper derives a new simplified relationship between the forward and the backward stages to avoid repetitive computations using the inherent orthogonal properties of the least squares methods. Furthermore, a new term exchanging scheme for backward model refinement is introduced to reduce computational demand. Finally, given the error reduction ratio criterion, effective and efficient forward and backward subset selection procedures are proposed. Extensive examples are presented to demonstrate the improved model compactness constructed by the proposed technique in comparison with some popular methods.
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This paper considers the antecedents and outcomes of downstream environmental logistics practices within green supply chain management amongst a sample of respondents based in the UK food industry. Framed through the conceptual lens of the natural resource-based view (NRBV) this research specifically considers (i) whether environmentally proactive companies implement environmental practices downstream in their supply chains as an extension of internal environmental practices and (ii) whether such downstream environmental practices influence performance, particularly when there has been engagement with key stakeholders in their implementation. The paper begins by developing a theoretical model grounded in the NRBV. This model and associated hypotheses are tested using Multivariate Ordinary Least Square (OLS) regression analysis using data from a sample of 149 firms within the UK food industry. The results provide support for a number of the assumptions implicit in the NRBV confirming the link between environmental proactivity and downstream environmental logistics and the important role of internal environmental practices in facilitating this link. The findings also support a direct link between downstream environmental logistics and both environmental and cost performance, which may be enhanced in the presence of high levels of environmental engagement with customers.
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Introdução: O declínio do equilíbrio, da força dos membros inferiores e o medo de cair são fatores de risco de queda associados ao envelhecimento e a sua avaliação pode ser realizada pelo teste One Leg Standing (OLS), Sit to Stand (STS) e pela Falls Eficacy Scale (FES), respetivamente. As aplicações para smartphone constituem uma alternativa para a avaliação dos fatores de risco de queda no envelhecimento. Objetivo: Analisar a capacidade de uma aplicação para smartphone na avaliação dos testes STS, OLS e FES. Metodologia: Realizou-se um estudo analítico numa amostra de 27 voluntários com idade ≥ 60 anos. Realizaram-se os testes STS, OLS e a FES (versão iconográfica, apresentada no smartphone). Os dados foram recolhidos simultaneamente por um smartphone e pelo Qualisys Motion Capture Systems associado a uma plataforma de forças. Foi utilizado o r de Pearson ou Spearman para analisar as possíveis correlações. Resultados: No STS obteve-se uma correlação muito forte (rp=0.97) no número de repetições de ciclos Sit Stand Sit (SLS) e forte na duração média do SLS (rp=0.85) e das subfases Sit to Stand (rp=0.69) e Stand to Sit (rp=0.778), com p<0.001. As medidas de inclinação do tronco apresentaram correlações fortes, com exceção do ângulo inicial (p≥0.05). No OLS, verificou-se uma correlação moderada entre o deslocamento do centro de pressão peak to peak médio-lateral (rs=0.45; p=0.017) e antero-posterior (rs=0.39; p=0.046), root mean square médio-lateral (rs=0.39; p=0.046) e antero-posterior (rs=0.46; p=0.017) e área do estatocinesiograma (rs=0.45; p=0.018). Na FES obteve-se uma correlação moderada em três categorias: ‘tomar banho/duche’ (rs=0.49; p=0.010), ‘deitar/levantar da cama (rs=0.43; p=0.024) e ‘chegar aos armários’ (rs=0.38; p=0.050). Conclusão: A aplicação para smartphone parece avaliar corretamente os ciclos e a variação da inclinação do tronco no STS, porém parece necessitar de ser reajustada na FES e na velocidade do deslocamento do centro de pressão, no OLS.
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Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia
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Durante as últimas décadas observou-se o crescimento da importância das avaliações fornecidas pelas agências de rating, sendo este um fator decisivo na tomada de decisão dos investidores. Também os emitentes de dívida são largamente afetados pelas alterações das classificações atribuídas por estas agências. Esta investigação pretende, por um lado, compreender se estas agências têm poder para conseguirem influenciar a evolução da dívida pública e qual o seu papel no mercado financeiro. Por outro, pretende compreender quais os fatores determinantes da dívida pública portuguesa, bem como a realização de uma análise por percentis com o objetivo de lhe atribuir um rating. Para a análise dos fatores que poderão influenciar a dívida pública, a metodologia utilizada é uma regressão linear múltipla estimada através do Método dos Mínimos Quadrados (Ordinary Least Squares – OLS), em que num cenário inicial era composta por onze variáveis independentes, sendo a dívida pública a variável dependente, para um período compreendido entre 1996 e 2013. Foram realizados vários testes ao modelo inicial, com o objetivo de encontrar um modelo que fosse o mais explicativo possível. Conseguimos ainda identificar uma relação inversa entre o rating atribuído por estas agências e a evolução da dívida pública, no sentido em que para períodos em que o rating desce, o crescimento da dívida é mais acentuado. Não nos foi, no entanto, possível atribuir um rating à dívida pública através de uma análise de percentis.
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Are return migrants more productive than non-migrants? If so, is it a causal effect or simply self-selection? Existing literature has not reached a consensus on the role of return migration for origin countries. To answer these research questions, an empirical analysis was performed based on household data collected in Cape Verde. One of the most common identification problems in the migration literature is the presence of migrant self-selection. In order to disentangle potential selection bias, we use instrumental variable estimation using variation provided by unemployment rates in migrant destination countries, which is compared with OLS and Nearest Neighbor Matching (NNM) methods. The results using the instrumental variable approach provide evidence of labour income gains due to return migration, while OLS underestimates the coefficient of interest. This bias points towards negative self-selection of return migrants on unobserved characteristics, although the different estimates cannot be distinguished statistically. Interestingly, migration duration and occupational changes after migration do not seem to influence post-migration income. There is weak evidence that return migrants from the United States have higher income gains caused by migration than the ones who returned from Portugal.
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This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.
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In this discussion OLS regressions are used to study the factors that influence sovereign yield spreads and domestic bank indeces for a set of euro area countries. The results show that common factors explain changes in bank indeces better than in the yields. Moreover, although there is some country differentiation, a common pattern among all is visible. A contemporary spillover effect between banks and sovereigns emerged after bank bailouts and became stronger with the burst of the sovereign debt crisis. The vicious cycle between the two has contributed to the escalation of spreads and to painful austerity measures.
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In this study we aim to investigate the health discrepancies arising from unequal economic status, known as the “wealth-health gradient”. Our sample comprises 47,163 individuals from 14 European countries in the SHARE Wave 4 (2011), representing the population aged 50 and older. Through a cross-sectional OLS regression model, we have tested the impact of country-level indicators to infer their effect on personal health and on the magnitude of the gradient. The results find that private expenditure yields, on average, a higher, but fast decreasing, health benefit than public expenditure; and that income inequality is irrelevant for reducing health inequalities.
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The existence of competition policy forces companies to adjust their behaviour. This is also costly. Using a database from a company on contracts, I will try to estimate if a specific competition policy disposition, supply contracts cannot be longer than 60 months, has costs for the coffee suppliers operating in the Portuguese “on-trade” coffee market. The estimation method used in this paper will be OLS. The results suggest that limiting the duration of exclusivity contracts to 60 months can be harmful to the coffee suppliers and it can even seriously affect the market functioning. Key
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The purpose of this study was to identify the impact of stressors and offsetting satistiers, measured in this study with Stress Offset Score (SOS), on intentions to quit and examine the mediating and moderating effects of three facets of work satisfaction (job satisfaction, pay satisfaction, and satisfaction with supervisor) and two facets of organizational commitment (affective and nonnative commitment) on this relationship. The sample was composed of 2990 employees from 21 public and private organizations. The interaction of each type of work satisfaction and organizational commitment, with SOS, was tested using Ordinary Least Squares (OLS) procedures. Intentions to quit was the dependent variable. The research questions were determine: (1) Does SOS predict intentions to quit? (2) Does work satisfaction mediate the predictive relationship of SOS on intentions to quit? (3) Does organizational commitment mediate the predictive relationship of SOS on intent to quit? (4) Does work satisfaction moderate the predictive relationship of SOS on intentions to quit? and (5) Does organizational commitment moderate the predictive relationship of SOS on intentions to quit? The results indicated that SOS was negatively correlated with intentions to quit. Each of the types of work satisfaction and organizational commitment variables showed a partial mediated relationship with SOS and each relationship was highly significant, while normative commitment explained more of the relationship then other mediators. The study also tested for interactions but no statistical significant relationships where established between any of the interaction terms (e.g., SOSxJob Satisfaction and SOSxAffcctive Commitment) and intentions to quit.
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We explored the potential mediating influence of physical fitness on the relationship between academic performance and motor proficiency in children. 1864 students (F:926, M:938, age 11.91 (SD:0.34). Academic achievement was derived from an average of standardized tests of reading, writing, and math. The Bruininks-Oseretsky Test of Motor Performance (short-form) determined motor proficiency. Fitness (peak oxygen uptake) was established with the Léger 20-m Shuttle Run Test. OLS regression identified several significant predictors of academic performance. After controlling for age (p=0.0135), gender (p<0.0001), and parental education (p<0.0001), motor proficiency (p<0.0001), was significant. After adding physical fitness (p=0.0030) to the model the effect of motor proficiency remained significant however the point estimate was reduced from 0.0034 (p<0.0001) to 0.0026 (p<0.0001). These results suggest that physical fitness plays a mediating role on the relationship between academic performance and motor proficiency although both aerobic fitness and motor proficiency have independent roles.
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The Dudding group is interested in the application of Density Functional Theory (DFT) in developing asymmetric methodologies, and thus the focus of this dissertation will be on the integration of these approaches. Several interrelated subsets of computer aided design and implementation in catalysis have been addressed during the course of these studies. The first of the aims rested upon the advancement of methodologies for the synthesis of biological active C(1)-chiral 3-methylene-indan-1-ols, which in practice lead to the use of a sequential asymmetric Yamamoto-Sakurai-Hosomi allylation/Mizoroki Heck reaction sequence. An important aspect of this work was the utilization of ortho-substituted arylaldehyde reagents which are known to be a problematic class of substrates for existing asymmetric allylation approaches. The second phase of my research program lead to the further development of asymmetric allylation methods using o-arylaldehyde substrates for synthesis of chiral C(3)-substituted phthalides. Apart from the de novo design of these chemistries in silico, which notably utilized water-tolerant, inexpensive, and relatively environmental benign indium metal, this work represented the first computational study of a stereoselective indium-mediated process. Following from these discoveries was the advent of a related, yet catalytic, Ag(I)-catalyzed approach for preparing C(3)-substituted phthalides that from a practical standpoint was complementary in many ways. Not only did this new methodology build upon my earlier work with the integrated (experimental/computational) use of the Ag(I)-catalyzed asymmetric methods in synthesis, it provided fundamental insight arrived at through DFT calculations, regarding the Yamamoto-Sakurai-Hosomi allylation. The development of ligands for unprecedented asymmetric Lewis base catalysis, especially asymmetric allylations using silver and indium metals, followed as a natural extension from these earlier discoveries. To this end, forthcoming as well was the advancement of a family of disubstituted (N-cyclopropenium guanidine/N-imidazoliumyl substituted cyclopropenylimine) nitrogen adducts that has provided fundamental insight into chemical bonding and offered an unprecedented class of phase transfer catalysts (PTC) having far-reaching potential. Salient features of these disubstituted nitrogen species is unprecedented finding of a cyclopropenium based C-H•••πaryl interaction, as well, the presence of a highly dissociated anion projected them to serve as a catalyst promoting fluorination reactions. Attracted by the timely development of these disubstituted nitrogen adducts my last studies as a PhD scholar has addressed the utility of one of the synthesized disubstituted nitrogen adducts as a valuable catalyst for benzylation of the Schiff base N-diphenyl methylene glycine ethyl ester. Additionally, the catalyst was applied for benzylic fluorination, emerging from this exploration was successful fluorination of benzyl bromide and its derivatives in high yields. A notable feature of this protocol is column-free purification of the product and recovery of the catalyst to use in a further reaction sequence.