918 resultados para dynamic factor models


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XACb0070 is an uncharacterized protein coded by the two large plasmids isolated from Xanthomonas axonopodis pv. cirri, the agent of citrus canker and responsible for important economical losses in citrus world production. XACb0070 presents sequence homology only with other hypothetical proteins belonging to plant pathogens, none of which have their structure determined. The NMR-derived solution structure reveals this protein is a homodimer in which each monomer presents two domains with different structural and dynamic properties: a folded N-terminal domain with beta alpha alpha topology which mediates dimerization and a long disordered C-terminal tail. The folded domain shows high structural similarity to the ribbon-helix-helix transcriptional repressors, a family of DNA-binding proteins of conserved 3D fold but low sequence homology: indeed XACb0070 binds DNA. Primary sequence and fold comparison of XACb0070 with other proteins of the ribbon-helix-helix family together with examination of the genes in the vicinity of xacb0070 suggest the protein might be the component of a toxin-antitoxin system. (C) 2010 Elsevier Inc. All rights reserved.

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RpfG is a paradigm for a class of widespread bacterial two-component regulators with a CheY-like receiver domain attached to a histidine-aspartic acid-glycine-tyrosine-proline (HD-GYP) cyclic di-GMP phosphodiesterase domain. In the plant pathogen Xanthomonas campestris pv. campestris (Xcc), a two-component system comprising RpfG and the complex sensor kinase RpfC is implicated in sensing and responding to the diffusible signaling factor (DSF), which is essential for cell-cell signaling. RpfF is involved in synthesizing DSF, and mutations of rpfF, rpfG, or rpfC lead to a coordinate reduction in the synthesis of virulence factors such as extracellular enzymes, biofilm structure, and motility. Using yeast two-hybrid analysis and fluorescence resonance energy transfer experiments in Xcc, we show that the physical interaction of RpfG with two proteins with diguanylate cyclase (GGDEF) domains controls a subset of RpfG-regulated virulence functions. RpfG interactions were abolished by alanine substitutions of the three residues of the conserved GYP motif in the HD-GYP domain. Changing the GYP motif or deletion of the two GGDEF-domain proteins reduced Xcc motility but not the synthesis of extracellular enzymes or biofilm formation. RpfG-GGDEF interactions are dynamic and depend on DSF signaling, being reduced in the rpfF mutant but restored by DSF addition. The results are consistent with a model in which DSF signal transduction controlling motility depends on a highly regulated, dynamic interaction of proteins that influence the localized expression of cyclic di-GMP.

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The fluorescence quenching kinetics of two porphyrin dendrimer series (GnTPPH(2) and GnPZn) by different type of quenchers is reported. The microenvironment surrounding the core in GnPZn was probing by core-quencher interactions using benzimidazole. The dependence of quencher binding constant (K(a) ) on generation indicates the presence of a weak interaction between branches and the core of the porphyrin dendrimer. The similar free volume in dendrimers of third and fourth generation suggests that structural collapse in high generations occurs by packing of the dendrimer peripheral layer. Dynamic fluorescence quenching of the porphyrin core by 1,3-dicyanomethylene-2-methyl-2-pentyl-indan (PDCMI) in GnTPPH(2) is a distance dependent electron transfer process with an exponential attenuation factor beta=0.33 angstrom(-1). The quenching by 1,2-dibromobenzene occurs by diffusion process of the quencher toward to the porphyrin core, and its rate constant is practically independent of dendrimer generation.

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The possibility to compress analyte bands at the beginning of CE runs has many advantages. Analytes at low concentration can be analyzed with high signal-to-noise ratios by using the so-called sample stacking methods. Moreover, sample injections with very narrow initial band widths (small initial standard deviations) are sometimes useful, especially if high resolutions among the bands are required in the shortest run time. In the present work, a method of sample stacking is proposed and demonstrated. It is based on BGEs with high thermal sensitive pHs (high dpH/dT) and analytes with low dpK(a)/dT. High thermal sensitivity means that the working pK(a) of the BGE has a high dpK(a)/dT in modulus. For instance, Tris and Ethanolamine have dpH/dT = -0.028/degrees C and -0.029/degrees C, respectively, whereas carboxylic acids have low dpK(a)/dT values, i.e. in the -0.002/degrees C to+0.002/degrees C range. The action of cooling and heating sections along the capillary during the runs affects also the local viscosity, conductivity, and electric field strength. The effect of these variables on electrophoretic velocity and band compression is theoretically calculated using a simple model. Finally, this stacking method was demonstrated for amino acids derivatized with naphthalene-2,3-dicarboxaldehyde and fluorescamine using a temperature difference of 70 degrees C between two neighbor sections and Tris as separation buffer. In this case, the BGE has a high pH thermal coefficient whereas the carboxylic groups of the analytes have low pK(a) thermal coefficients. The application of these dynamic thermal gradients increased peak height by a factor of two (and decreased the standard deviations of peaks by a factor of two) of aspartic acid and glutamic acid derivatized with naphthalene-2,3-dicarboxaldehyde and serine derivatized with fluorescamine. The effect of thermal compression of bands was not observed when runs were accomplished using phosphate buffer at pH 7 (negative control). Phosphate has a low dpH/dT in this pH range, similar to the dK(a)/dT of analytes. It is shown that vertical bar dK(a)/dT-dpH/dT vertical bar >> 0 is one determinant factor to have significant stacking produced by dynamic thermal junctions.

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AIMS/HYPOTHESIS: Soluble tumor necrosis factor receptors 1 and 2 (sTNFR1 and sTNFR2) contribute to experimental diabetic kidney disease, a condition with substantially increased cardiovascular risk when present in patients. Therefore, we aimed to explore the levels of sTNFRs, and their association with prevalent kidney disease, incident cardiovascular disease, and risk of mortality independently of baseline kidney function and microalbuminuria in a cohort of patients with type 2 diabetes. In pre-defined secondary analyses we also investigated whether the sTNFRs predict adverse outcome in the absence of diabetic kidney disease. METHODS: The CARDIPP study, a cohort study of 607 diabetes patients [mean age 61 years, 44 % women, 45 cardiovascular events (fatal/non-fatal myocardial infarction or stroke) and 44 deaths during follow-up (mean 7.6 years)] was used. RESULTS: Higher sTNFR1 and sTNFR2 were associated with higher odds of prevalent kidney disease [odd ratio (OR) per standard deviation (SD) increase 1.60, 95 % confidence interval (CI) 1.32-1.93, p < 0.001 and OR 1.54, 95 % CI 1.21-1.97, p = 0.001, respectively]. In Cox regression models adjusting for age, sex, glomerular filtration rate and urinary albumin/creatinine ratio, higher sTNFR1 and sTNFR2 predicted incident cardiovascular events [hazard ratio (HR) per SD increase, 1.66, 95 % CI 1.29-2.174, p < 0.001 and HR 1.47, 95 % CI 1.13-1.91, p = 0.004, respectively]. Results were similar in separate models with adjustments for inflammatory markers, HbA1c, or established cardiovascular risk factors, or when participants with diabetic kidney disease at baseline were excluded (p < 0.01 for all). Both sTNFRs were associated with mortality. CONCLUSIONS/INTERPRETATIONS: Higher circulating sTNFR1 and sTNFR2 are associated with diabetic kidney disease, and predicts incident cardiovascular disease and mortality independently of microalbuminuria and kidney function, even in those without kidney disease. Our findings support the clinical utility of sTNFRs as prognostic markers in type 2 diabetes.

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The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude.

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In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.

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Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.

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Several works in the shopping-time and in the human-capital literature, due to the nonconcavity of the underlying Hamiltonian, use Örst-order conditions in dynamic optimization to characterize necessity, but not su¢ ciency, in intertemporal problems. In this work I choose one paper in each one of these two areas and show that optimality can be characterized by means of a simple aplication of Arrowís (1968) su¢ ciency theorem.

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This paper confronts the Capital Asset Pricing Model - CAPM - and the 3-Factor Fama-French - FF - model using both Brazilian and US stock market data for the same Sample period (1999-2007). The US data will serve only as a benchmark for comparative purposes. We use two competing econometric methods, the Generalized Method of Moments (GMM) by (Hansen, 1982) and the Iterative Nonlinear Seemingly Unrelated Regression Estimation (ITNLSUR) by Burmeister and McElroy (1988). Both methods nest other options based on the procedure by Fama-MacBeth (1973). The estimations show that the FF model fits the Brazilian data better than CAPM, however it is imprecise compared with the US analog. We argue that this is a consequence of an absence of clear-cut anomalies in Brazilian data, specially those related to firm size. The tests on the efficiency of the models - nullity of intercepts and fitting of the cross-sectional regressions - presented mixed conclusions. The tests on intercept failed to rejected the CAPM when Brazilian value-premium-wise portfolios were used, contrasting with US data, a very well documented conclusion. The ITNLSUR has estimated an economically reasonable and statistically significant market risk premium for Brazil around 6.5% per year without resorting to any particular data set aggregation. However, we could not find the same for the US data during identical period or even using a larger data set. Este estudo procura contribuir com a literatura empírica brasileira de modelos de apreçamento de ativos. Dois dos principais modelos de apreçamento são Infrontados, os modelos Capital Asset Pricing Model (CAPM)e de 3 fatores de Fama-French. São aplicadas ferramentas econométricas pouco exploradas na literatura nacional na estimação de equações de apreçamento: os métodos de GMM e ITNLSUR. Comparam-se as estimativas com as obtidas de dados americanos para o mesmo período e conclui-se que no Brasil o sucesso do modelo de Fama e French é limitado. Como subproduto da análise, (i) testa-se a presença das chamadas anomalias nos retornos, e (ii) calcula-se o prêmio de risco implícito nos retornos das ações. Os dados revelam a presença de um prêmio de valor, porém não de um prêmio de tamanho. Utilizando o método de ITNLSUR, o prêmio de risco de mercado é positivo e significativo, ao redor de 6,5% ao ano.

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This dissertation proposes a bivariate markov switching dynamic conditional correlation model for estimating the optimal hedge ratio between spot and futures contracts. It considers the cointegration between series and allows to capture the leverage efect in return equation. The model is applied using daily data of future and spot prices of Bovespa Index and R$/US$ exchange rate. The results in terms of variance reduction and utility show that the bivariate markov switching model outperforms the strategies based ordinary least squares and error correction models.

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This doctoral dissertation analyzes two novels by the American novelist Robert Coover as examples of hypertextual writing on the book bound page, as tokens of hyperfiction. The complexity displayed in the novels, John's Wife and The Adventures of Lucky Pierre, integrates the cultural elements that characterize the contemporary condition of capitalism and technologized practices that have fostered a different subjectivity evidenced in hypertextual writing and reading, the posthuman subjectivity. The models that account for the complexity of each novel are drawn from the concept of strange attractors in Chaos Theory and from the concept of rhizome in Nomadology. The transformations the characters undergo in the degree of their corporeality sets the plane on which to discuss turbulence and posthumanity. The notions of dynamic patterns and strange attractors, along with the concept of the Body without Organs and Rhizome are interpreted, leading to the revision of narratology and to analytical categories appropriate to the study of the novels. The reading exercised throughout this dissertation enacts Daniel Punday's corporeal reading. The changes in the characters' degree of materiality are associated with the stages of order, turbulence and chaos in the story, bearing on the constitution of subjectivity within and along the reading process. Coover's inscription of planes of consistency to counter linearity and accommodate hypertextual features to the paper supported narratives describes the characters' trajectory as rhizomatic. The study led to the conclusion that narrative today stands more as a regime in a rhizomatic relation with other regimes in cultural practice than as an exclusively literary form and genre. Besides this, posthuman subjectivity emerges as class identity, holding hypertextual novels as their literary form of choice.

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We show that Judd (1982)’s method can be applied to any finite system, contrary to what he claimed in 1987. An example shows how to employ the technic to study monetary models in presence of capital accumulation.

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This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.

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Em modelos de competição de preços, somente um custo de procura positivo por parte do consumidor não gera equilíbrio com dispersão de preços. Já modelos dinâmicos de switching cost consistentemente geram este fenômeno bastante documentado para preços no varejo. Embora ambas as literaturas sejam vastas, poucos modelos tentaram combinar as duas fricções em um só modelo. Este trabalho apresenta um modelo dinâmico de competição de preços em que consumidores idênticos enfrentam custos de procura e de switching. O equilíbrio gera dispersão nos preços. Ainda, como os consumidores são obrigados a se comprometer com uma amostra fixa de firmas antes dos preços serem definidos, somente dois preços serão considerados antes de cada compra. Este resultado independe do tamanho do custo de procura individual do consumidor.