999 resultados para Dynamic Localization


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In recent years, one of the most significant progress in the understanding of liver diseases was the demonstration that liver fibrosis is a dynamic process resulting from a balance between synthesis and degradation of several matrix components, collagen in particular. Thus, fibrosis has been found to be a very early event during liver diseases, be it of toxic, viral or parasitic origin, and to be spontaneously reversible, either partially or totally. In liver fibrosis cell matrix interactions are dependent on the existence of the many factors (sometimes acting in combination) which produce the same events at the cellular and molecular levels. These events are: (i) the recruitment of fiber-producing cells, (ii) their proliferation, (iii) the secretion of matrix constituents of the extracellular matrix, and (iv) the remodeling and degradation of the newly formed matrix. All these events represent, at least in principle, a target for a therapeutic intervention aimed at influencing the experimentally induced hepatic fibrosis. In this context, hepatosplenic schistosomiasis is of particular interest, being an immune cell-mediated granulomatous disease and a model of liver fibrosis allowing extensive studies in human and animals as well as providing original in vitro models.

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Auditory spatial functions, including the ability to discriminate between the positions of nearby sound sources, are subserved by a large temporo-parieto-frontal network. With the aim of determining whether and when the parietal contribution is critical for auditory spatial discrimination, we applied single pulse transcranial magnetic stimulation on the right parietal cortex 20, 80, 90 and 150 ms post-stimulus onset while participants completed a two-alternative forced choice auditory spatial discrimination task in the left or right hemispace. Our results reveal that transient TMS disruption of right parietal activity impairs spatial discrimination when applied at 20 ms post-stimulus onset for sounds presented in the left (controlateral) hemispace and at 80 ms for sounds presented in the right hemispace. We interpret our finding in terms of a critical role for controlateral temporo-parietal cortices over initial stages of the building-up of auditory spatial representation and for a right hemispheric specialization in integrating the whole auditory space over subsequent, higher-order processing stages.

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This paper shows that tourism specialisation can help to explain the observed high growth rates of small countries. For this purpose, two models of growth and trade are constructed to represent the trade relations between two countries. One of the countries is large, rich, has an own source of sustained growth and produces a tradable capital good. The other is a small poor economy, which does not have an own engine of growth and produces tradable tourism services. The poor country exports tourism services to and imports capital goods from the rich economy. In one model tourism is a luxury good, while in the other the expenditure elasticity of tourism imports is unitary. Two main results are obtained. In the long run, the tourism country overcomes decreasing returns and permanently grows because its terms of trade continuously improve. Since the tourism sector is relatively less productive than the capital good sector, tourism services become relatively scarcer and hence more expensive than the capital good. Moreover, along the transition the growth rate of the tourism economy holds well above the one of the rich country for a long time. The growth rate differential between countries is particularly high when tourism is a luxury good. In this case, there is a faster increase in the tourism demand. As a result, investment of the small economy is boosted and its terms of trade highly improve.

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We give sufficient conditions for homotopical localization functors to preserve algebras over coloured operads in monoidal model categories. Our approach encompasses a number of previous results about preservation of structures under localizations, such as loop spaces or infinite loop spaces, and provides new results of the same kind. For instance, under suitable assumptions, homotopical localizations preserve ring spectra (in the strict sense, not only up to homotopy), modules over ring spectra, and algebras over commutative ring spectra, as well as ring maps, module maps, and algebra maps. It is principally the treatment of module spectra and their maps that led us to the use of coloured operads (also called enriched multicategories) in this context.

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We extend a reduced form model for pricing pass-through mortgage backed securities (MBS) and provide a novel hedging tool for investors in this market. To calculate the price of an MBS, traders use what is known as option-adjusted spread (OAS). The resulting OAS value represents the required basis points adjustment to reference curve discounting rates needed to match an observed market price. The OAS suffers from some drawbacks. For example, it remains constant until the maturity of the bond (thirty years in mortgage-backed securities), and does not incorporate interest rate volatility. We suggest instead what we call dynamic option adjusted spread (DOAS). The latter allows investors in the mortgage market to account for both prepayment risk and changes of the yield curve.

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AIMS: Estimates of the left ventricular ejection fraction (LVEF) in patients with life-threatening ventricular arrhythmias related to coronary artery disease (CAD) have rarely been reported despite it has become the basis for determining patient's eligibility for prophylactic defibrillator. We aimed to determine the extent and distribution of reduced LVEF in patients with sustained ventricular tachycardia or ventricular fibrillation. METHODS AND RESULTS: 252 patients admitted for ventricular arrhythmia related to CAD were included: 149 had acute myocardial infarction (MI) (Group I, 59%), 54 had significant chronic obstructive CAD suggestive of an ischaemic arrhythmic trigger (Group II, 21%) and 49 patients had an old MI without residual ischaemia (Group III, 19%). 34% of the patients with scar-related arrhythmias had an LVEF > or =40%. Based on pre-event LVEF evaluation, it can be estimated that less than one quarter of the whole study population had a known chronic MI with severely reduced LVEF. In Group III, the proportion of inferior MI was significantly higher than anterior MI (81 vs. 19%; absolute difference, -62; 95% confidence interval, -45 to -79; P < or = 0.0001), though median LVEF was higher in inferior MI (0.37 +/- 10 vs. 0.29 +/- 10; P = 0.0499). CONCLUSION: Patients included in defibrillator trials represent only a minority of the patients at risk of sudden cardiac death. By applying the current risk stratification strategy based on LVEF, more than one third of the patients with old MI would not have qualified for a prophylactic defibrillator. Our study also suggests that inferior scars may be more prone to ventricular arrhythmia compared to anterior scars.

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We extend a reduced form model for pricing pass-through mortgage backed securities (MBS) and provide a novel hedging tool for investors in this market. To calculate the price of an MBS, traders use what is known as option-adjusted spread (OAS). The resulting OAS value represents the required basis points adjustment to reference curve discounting rates needed to match an observed market price. The OAS suffers from some drawbacks. For example, it remains constant until the maturity of the bond (thirty years in mortgage-backed securities), and does not incorporate interest rate volatility. We suggest instead what we call dynamic option adjusted spread (DOAS), which allows investors in the mortgage market to account for both prepayment risk and changes of the yield curve.

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Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

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National inflation rates reflect domestic and international (regional and global) influences. The relative importance of these components remains a controversial empirical issue. We extend the literature on inflation co-movement by utilising a dynamic factor model with stochastic volatility to account for shifts in the variance of inflation and endogenously determined regional groupings. We find that most of inflation variability is explained by the country specific disturbance term. Nevertheless, the contribution of the global component in explaining industrialised countries’ inflation rates has increased over time.

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Using a standard open economy DSGE model, it is shown that the timing of asset trade relative to policy decisions has a potentially important impact on the welfare evaluation of monetary policy at the individual country level. If asset trade in the initial period takes place before the announcement of policy, a national policymaker can choose a policy rule which reduces the work effort of households in the policymaker’s country in the knowledge that consumption is fully insured by optimally chosen international portfolio positions. But if asset trade takes place after the policy announcement, this insurance is absent and households in the policymaker’s country bear the full consumption consequences of the chosen policy rule. The welfare incentives faced by national policymakers are very different between the two cases. Numerical examples confirm that asset market timing has a significant impact on the optimal policy rule.

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This study examines the impact of globalization on cross-country inequality and poverty using a panel data set for 65 developing counties, over the period 1970-2008. With separate modelling for poverty and inequality, explicit control for financial intermediation, and comparative analysis for developing countries, the study attempts to provide a deeper understanding of cross country variations in income inequality and poverty. The major findings of the study are five fold. First, a non-monotonic relationship between income distribution and the level of economic development holds in all samples of countries. Second, both openness to trade and FDI do not have a favourable effect on income distribution in developing countries. Third, high financial liberalization exerts a negative and significant influence on income distribution in developing countries. Fourth, inflation seems to distort income distribution in all sets of countries. Finally, the government emerges as a major player in impacting income distribution in developing countries.

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We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.