954 resultados para multi-factor authentication


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Epoxy resin bonded mica splitting is the insulation of choice for machine stators. However, this system is seen to be relatively weak under time varying mechanical stress, in particular the vibration causing delamination of mica and deboning of mica from the resin matrix. The situation is accentuated under the combined action of electrical, thermal and mechanical stress. Physical and probabilistic models for failure of such systems have been proposed by one of the authors of this paper earlier. This paper presents a pragmatic accelerated failure data acquisition and analytical paradigm under multi factor coupled stress, Electrical, Thermal. The parameters of the phenomenological model so developed are estimated based on sound statistical treatment of failure data.

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We performed Gaussian network model based normal mode analysis of 3-dimensional structures of multiple active and inactive forms of protein kinases. In 14 different kinases, a more number of residues (1095) show higher structural fluctuations in inactive states than those in active states (525), suggesting that, in general, mobility of inactive states is higher than active states. This statistically significant difference is consistent with higher crystallographic B-factors and conformational energies for inactive than active states, suggesting lower stability of inactive forms. Only a small number of inactive conformations with the DFG motif in the ``in'' state were found to have fluctuation magnitudes comparable to the active conformation. Therefore our study reports for the first time, intrinsic higher structural fluctuation for almost all inactive conformations compared to the active forms. Regions with higher fluctuations in the inactive states are often localized to the aC-helix, aG-helix and activation loop which are involved in the regulation and/or in structural transitions between active and inactive states. Further analysis of 476 kinase structures involved in interactions with another domain/protein showed that many of the regions with higher inactive-state fluctuation correspond to contact interfaces. We also performed extensive GNM analysis of (i) insulin receptor kinase bound to another protein and (ii) holo and apo forms of active and inactive conformations followed by multi-factor analysis of variance. We conclude that binding of small molecules or other domains/proteins reduce the extent of fluctuation irrespective of active or inactive forms. Finally, we show that the perceived fluctuations serve as a useful input to predict the functional state of a kinase.

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Contexte - La prévalence de la maladie de Crohn (MC), une maladie inflammatoire chronique du tube digestif, chez les enfants canadiens se situe parmi les plus élevées au monde. Les interactions entre les réponses immunes innées et acquises aux microbes de l'hôte pourraient être à la base de la transition de l’inflammation physiologique à une inflammation pathologique. Le leucotriène B4 (LTB4) est un modulateur clé de l'inflammation et a été associé à la MC. Nous avons postulé que les principaux gènes impliqués dans la voie métabolique du LTB4 pourrait conférer une susceptibilité accrue à l'apparition précoce de la MC. Dans cette étude, nous avons exploré les associations potentielles entre les variantes de l'ADN des gènes ALOX5 et CYP4F2 et la survenue précoce de la MC. Nous avons également examiné si les gènes sélectionnés montraient des effets parent-d'origine, influençaient les phénotypes cliniques de la MC et s'il existait des interactions gène-gène qui modifieraient la susceptibilité à développer la MC chez l’enfant. Méthodes – Dans le cadre d’une étude de cas-parents et de cas-témoins, des cas confirmés, leurs parents et des contrôles ont été recrutés à partir de trois cliniques de gastro-entérologie à travers le Canada. Les associations entre les polymorphismes de remplacement d'un nucléotide simple (SNP) dans les gènes CYP4F2 et ALOX5 ont été examinées. Les associations allélique et génotypiques ont été examinées à partir d’une analyse du génotype conditionnel à la parenté (CPG) pour le résultats cas-parents et à l’aide de table de contingence et de régression logistique pour les données de cas-contrôles. Les interactions gène-gène ont été explorées à l'aide de méthodes de réduction multi-factorielles de dimensionnalité (MDR). Résultats – L’étude de cas-parents a été menée sur 160 trios. L’analyse CPG pour 14 tag-SNP (10 dans la CYP4F2 et 4 dans le gène ALOX5) a révélé la présence d’associations alléliques ou génotypique significatives entre 3 tag-SNP dans le gène CYP4F2 (rs1272, p = 0,04, rs3093158, p = 0.00003, et rs3093145, p = 0,02). Aucune association avec les SNPs de ALOX5 n’a pu être démontrée. L’analyse de l’haplotype de CYP4F2 a montré d'importantes associations avec la MC (test omnibus p = 0,035). Deux haplotypes (GAGTTCGTAA, p = 0,05; GGCCTCGTCG, p = 0,001) montraient des signes d'association avec la MC. Aucun effet parent-d'origine n’a été observé. Les tentatives de réplication pour trois SNPs du gene CYP4F2 dans l'étude cas-témoins comportant 225 cas de MC et 330 contrôles suggèrent l’association dans un de ceux-ci (rs3093158, valeur non-corrigée de p du test unilatéral = 0,03 ; valeur corrigée de p = 0.09). La combinaison des ces deux études a révélé des interactions significatives entre les gènes CYP4F2, ALOX et NOD2. Nous n’avons pu mettre en évidence aucune interaction gène-sexe, de même qu’aucun gène associé aux phénotypes cliniques de la MC n’a pu être identifié. Conclusions - Notre étude suggère que la CYP4F2, un membre clé de la voie métabolique LTB4 est un gène candidat potentiel pour MC. Nous avons également pu mettre en évidence que les interactions entre les gènes de l'immunité adaptative (CYP4F2 et ALOX5) et les gènes de l'immunité innée (NOD2) modifient les risques de MC chez les enfants. D'autres études sur des cohortes plus importantes sont nécessaires pour confirmer ces conclusions.

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This case study on the Sifnos island, Greece, assesses the main factors controlling vegetation succession following crop abandonment and describes the vegetation dynamics of maquis and phrygana formations in relation to alternative theories of secondary succession. Field survey data were collected and analysed at community as well as species level. The results show that vegetation succession on abandoned crop fields is determined by the combined effects of grazing intensity, soil and geological characteristics and time. The analysis determines the quantitative grazing thresholds that modify the successional pathway. Light grazing leads to dominance by maquis vegetation while overgrazing leads to phryganic vegetation. The proposed model shows that vegetation succession following crop abandonment is a complex multi-factor process where the final or the stable stage of the process is not predefined but depends on the factors affecting succession. An example of the use of succession models and disturbance thresholds as a policy assessment tool is presented by evaluating the likely vegetation impacts of the recent reform of the Common Agricultural Policy on Sifnos island over a 20-30-year time horizon. (c) 2006 Elsevier B.V. All rights reserved.

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This study examines the relation between corporate social performance and stock returns in the UK. We closely evaluate the interactions between social and financial performance with a set of disaggregated social performance indicators for environment, employment, and community activities instead of using an aggregate measure. While scores on a composite social performance indicator are negatively related to stock returns, we find the poor financial reward offered by such firms is attributable to their good social performance on the environment and, to a lesser extent, the community aspects. Considerable abnormal returns are available from holding a portfolio of the socially least desirable stocks. These relationships between social and financial performance can be rationalized by multi-factor models for explaining the cross-sectional variation in returns, but not by industry effects.

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Multi-factor approaches to analysis of real estate returns have, since the pioneering work of Chan, Hendershott and Sanders (1990), emphasised a macro-variables approach in preference to the latent factor approach that formed the original basis of the arbitrage pricing theory. With increasing use of high frequency data and trading strategies and with a growing emphasis on the risks of extreme events, the macro-variable procedure has some deficiencies. This paper explores a third way, with the use of an alternative to the standard principal components approach – independent components analysis (ICA). ICA seeks higher moment independence and maximises in relation to a chosen risk parameter. We apply an ICA based on kurtosis maximisation to weekly US REIT data using a kurtosis maximising algorithm. The results show that ICA is successful in capturing the kurtosis characteristics of REIT returns, offering possibilities for the development of risk management strategies that are sensitive to extreme events and tail distributions.

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This thesis is an empirical-based study of the European Union’s Emissions Trading Scheme (EU ETS) and its implications in terms of corporate environmental and financial performance. The novelty of this study includes the extended scope of the data coverage, as most previous studies have examined only the power sector. The use of verified emissions data of ETS-regulated firms as the environmental compliance measure and as the potential differentiating criteria that concern the valuation of EU ETS-exposed firms in the stock market is also an original aspect of this study. The study begins in Chapter 2 by introducing the background information on the emission trading system (ETS), which focuses on (i) the adoption of ETS as an environmental management instrument and (ii) the adoption of ETS by the European Union as one of its central climate policies. Chapter 3 surveys four databases that provide carbon emissions data in order to determine the most suitable source of the data to be used in the later empirical chapters. The first empirical chapter, which is also Chapter 4 of this thesis, investigates the determinants of the emissions compliance performance of the EU ETS-exposed firms through constructing the best possible performance ratio from verified emissions data and self-configuring models for a panel regression analysis. Chapter 5 examines the impacts on the EU ETS-exposed firms in terms of their equity valuation with customised portfolios and multi-factor market models. The research design takes into account the emissions allowance (EUA) price as an additional factor, as it has the most direct association with the EU ETS to control for the exposure. The final empirical Chapter 6 takes the investigation one step further, by specifically testing the degree of ETS exposure facing different sectors with sector-based portfolios and an extended multi-factor market model. The findings from the emissions performance ratio analysis show that the business model of firms significantly influences emissions compliance, as the capital intensity has a positive association with the increasing emissions-to-emissions cap ratio. Furthermore, different sectors show different degrees of sensitivity towards the determining factors. The production factor influences the performance ratio of the Utilities sector, but not the Energy or Materials sectors. The results show that the capital intensity has a more profound influence on the utilities sector than on the materials sector. With regard to the financial performance impact, ETS-exposed firms as aggregate portfolios experienced a substantial underperformance during the 2001–2004 period, but not in the operating period of 2005–2011. The results of the sector-based portfolios show again the differentiating effect of the EU ETS on sectors, as one sector is priced indifferently against its benchmark, three sectors see a constant underperformance, and three sectors have altered outcomes.

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Este trabalho tem por objetivo avaliar a influência dos parâmetros pressão, freqüência e fator de trabalho, bem como a interação destes fatores, na capacidade de gerar plasma estável e com propriedades nitretantes no interior de furos não passantes de pequeno diâmetro. Para atingir estes objetivos foram realizados experimentos utilizando um reator equipado com fonte de potência pulsada de 2 KW, mistura gasosa composta de 76% de Nitrogênio e 24% de Hidrogênio, amostras de aço ABNT 1045 normalizadas. As nitretações foram realizadas pelo período de uma hora a temperatura de 500 0C. Foram empregadas freqüências de 100, 1000 e 5000 Hz, fatores de trabalho de 0,5 (50%), 0,75 (75%), 1 (100%), as pressões utilizadas foram de 2, 3 e 4 Torr e furos não passantes de φ3 x 40 mm, φ4 x 60 mm, φ5 x 75 mm. Para determinar a significância de cada parâmetro e de suas interações foi utilizado o modelo estatístico Multi-Factor Anova, com projeto fatorial cruzado a 3 fatores e 3 níveis para cada fator. Com o uso do programa Statgraphics foram geradas as equações que mais se ajustaram ao modelo. Estas equações determinam a máxima profundidade de geração de plasma nitretante no interior dos furos de pequeno diâmetro para as condições de tratamento expostas acima.

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Com o objetivo de precificar derivativos de taxas de juros no mercado brasileiro, este trabalho foca na implementação do modelo de Heath, Jarrow e Morton (1992) em sua forma discreta e multifatorial através de uma abordagem numérica, e, que possibilita uma grande flexibilidade na estimativa da taxa forward sob uma estrutura de volatilidade baseada em fatores ortogonais, facilitando assim a simulação de sua evolução por Monte Carlo, como conseqüência da independência destes fatores. A estrutura de volatilidade foi construída de maneira a ser totalmente não paramétrica baseada em vértices sintéticos que foram obtidos por interpolação dos dados históricos de cotações do DI Futuro negociado na BM&FBOVESPA, sendo o período analisado entre 02/01/2003 a 28/12/2012. Para possibilitar esta abordagem foi introduzida uma modificação no modelo HJM desenvolvida por Brace e Musiela (1994).

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Multivariate Affine term structure models have been increasingly used for pricing derivatives in fixed income markets. In these models, uncertainty of the term structure is driven by a state vector, while the short rate is an affine function of this vector. The model is characterized by a specific form for the stochastic differential equation (SDE) for the evolution of the state vector. This SDE presents restrictions on its drift term which rule out arbitrages in the market. In this paper we solve the following inverse problem: Suppose the term structure of interest rates is modeled by a linear combination of Legendre polynomials with random coefficients. Is there any SDE for these coefficients which rules out arbitrages? This problem is of particular empirical interest because the Legendre model is an example of factor model with clear interpretation for each factor, in which regards movements of the term structure. Moreover, the Affine structure of the Legendre model implies knowledge of its conditional characteristic function. From the econometric perspective, we propose arbitrage-free Legendre models to describe the evolution of the term structure. From the pricing perspective, we follow Duffie et al. (2000) in exploring Legendre conditional characteristic functions to obtain a computational tractable method to price fixed income derivatives. Closing the article, the empirical section presents precise evidence on the reward of implementing arbitrage-free parametric term structure models: The ability of obtaining a good approximation for the state vector by simply using cross sectional data.

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Com o aumento do número de gestores especializados em um número cada vez maior de possibilidades de investimentos na indústria de fundos brasileira, os fundos Multigestor se tornaram uma alternativa para os investidores que procuram diversificar seus investimentos e delegam às instituições financeiras o trabalho de alocar os recursos dentro das diferentes estratégias e fundos existentes no mercado. O intuito deste estudo é avaliar a capacidade de gerar retornos anormais (alfa) dos fundos de fundos da indústria brasileira, classificados como Fundos Multimercados Multigestor. Para isso foi estudada uma amostra com 1.421 fundos Multigestor com tributação de Longo Prazo no período de janeiro de 2005 a dezembro de 2011. A análise dos resultados encontrados através de regressões de modelos de vários fatores, derivados do modelo de Jensen (1968), sugere que apenas 3,03% dos fundos estudados conseguem adicionar valor a seus cotistas. Foram estudadas ainda as três principais fontes potenciais de geração de alfa dos fundos de fundos, a escolha das estratégias que compõe a carteira do fundo (alocação estratégica), a antecipação de movimentos de mercado (market timing) e a capacidade selecionar os melhores fundos dentro de cada estratégia (seleção de fundos). A partir da inclusão de termos quadráticos, conforme proposto pelos modelos de Treynor e Mazuy (1966) pode-se verificar que os fundos Multigestor, em média, não conseguem adicionar valor tentando antecipar movimentos de mercado (market timing). Através da construção de uma variável explicativa com a composição estratégica de cada fundo da amostra em cada período de tempo, pode-se verificar que os gestores de fundos de fundos, em média, também fracassam ao tentar selecionar os melhores fundos/gestores da indústria. Já a escolha das estratégias que compõe a carteira do fundo (alocação estratégica) mostrou contribuir positivamente para o retorno dos fundos. Ainda foi avaliada a capacidade de gerar alfa antes dos custos, o que elevou o percentual de fundos com alfa positivo para 6,39% dos fundos estudados, mas foi incapaz de alterar o sinal do alfa médio, que permaneceu negativo.

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Includes bibliography

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Galina Kovaleva. The Formation of the Exchange Rate on the Russian Market: Dynamics and Modelling. The Russian financial market is fast becoming one of the major sectors of the Russian economy. Assets have been increasing steadily, while new market segments and new financial market instruments have emerged. Kovaleva attempted to isolate the factors influencing exchange rates, determine patterns in the dynamic changes to the rouble/dollar exchange rate, construct models of the processes, and on the basis of these activities make forecasts. She studied the significance of economic indicators influencing the rouble/dollar exchange rate at different times, and developed multi-factor econometric models. In order to reveal the inner structure of the financial indicators and to work out ex-post forecasts for different time intervals, she carried out a series of calculations with the aim of constructing trend-cyclical (TC) and harmonic models, and Box and Jenkins models. She found that: 1. The Russian financial market is dependant on the rouble/dollar exchange rate. Its dynamics are formed under the influence of the short-term state treasury notes and government bonds markets, interbank loans, the rouble/DM exchange rate, the inflation rate, and the DM/dollar exchange rate. The exchange rate is influenced by sales on the Moscow Interbank Currency Exchange and the mechanism of those sales. 2. The TC model makes it possible to conduct an in-depth study of the structure of the processes and to make forecasts of the dynamic changes to currency indicators. 3. The Russian market is increasingly influenced by the world currency market and its prospects are of crucial interest for the world financial community.

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The understanding of molecular mechanisms requires the elucidation of protein-­‐protein interaction in vivo. For large multi-­‐factor complexes like those assembling on mRNA, co-­‐immunoprecipitation assays often identify many peripheral interactors that complicate the interpretation of such results and that might conceal other insightful mechanistic connections. Here we address the protein-­‐protein interaction network for key factors in the nonsense-­‐mediated mRNA decay (NMD) pathway in a distant-­‐dependent manner using BioID1,2. In this novel approach, the mutant E. coli biotin-­‐protein ligase BirAR118G is fused to the bait protein and biotinylates proximal proteins promiscuously. Hence, interactors positioned close to the bait in vivo are enriched by streptavidin purification and identified by mass spectrometry or western blotting. We present a validation of the BioID assay and preliminary results for close interactors of UPF1 and other key players in NMD.