959 resultados para Quasi-orthogonal space-time block codes (STBCs)


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This thesis explores the importance of literary New York City in the urban narratives of Edith Wharton and Anzia Yezierska. It specifically looks at the Empire City of the Progressive Period when the concept of the city was not only a new theme but also very much a typical American one which was as central to the American experience as had been the Western frontier. It could be argued, in fact, that the American city had become the new frontier where modern experiences like urbanization, industrialization, immigration, and also women's emancipation and suffrage, caused all kinds of sensations on the human scale from smoothly lived assimilation and acculturation to deeply felt alienation because of the constantly shifting urban landscape. The developing urban space made possible the emergence of new female literary protagonists like the working girl, the reformer, the prostitute, and the upper class lady dedicating her life to 'conspicuous consumption'. Industrialization opened up city space to female exploration: on the one hand, upper and middle class ladies ventured out of the home because of the many novel urban possibilities, and on the other, lower class and immigrant girls also left their domestic sphere to look for paid jobs outside the home. New York City at the time was not only considered the epicenter of the world at large, it was also a city of great extremes. Everything was constantly in flux: small brownstones made way for ever taller skyscrapers and huge waves of immigrants from Europe pushed native New Yorkers further uptown on the island, adding to the crowdedness and intensity of the urban experience. The city became a polarized urban space with Fifth Avenue representing one end of the spectrum and the Lower East Side the other. Questions of space and the urban home greatly mattered. It has been pointed out that the city setting functions as an ideal means for the display of human nature as well as social processes. Narrative representations of urban space, therefore, provide a similar canvas for a protagonist's journey and development. From widely diverging vantage points both Edith Wharton and Anzia Yezierska thus create a polarized city where domesticity is a primal concern. Looking at all of their New York narratives by close readings of exterior and interior city representations, this thesis shows how urban space greatly affects questions of identity, assimilation, and alienation in literary protagonists who cannot escape the influence of their respective urban settings. Edith Wharton's upper class "millionaire" heroines are framed and contained by the city interiors of "old" New York, making it impossible for them to truly participate in the urban landscape in order to develop outside of their 'Gilt Cages'. On the other side are Anzia Yezierska's struggling "immigrant" protagonists who, against all odds, never give up in their urban context of streets, rooftops, and stoops. Their New York City, while always challenging and perpetually changing, at least allows them perspectives of hope for a 'Promised Land' in the making. Central for both urban narrative approaches is the quest for a home as an architectural structure, a spiritual resting place, and a locus for identity forming. But just as the actual city embraces change, urban protagonists must embrace change also if they desire to find fulfillment and success. That this turns out to be much easier for Anzia Yezierska's driven immigrants rather than for Edith Wharton's well established native New Yorkers is a surprising conclusion to this urban theme.

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Report for the scientific sojourn at the Department of Information Technology (INTEC) at the Ghent University, Belgium, from january to june 2007. All-Optical Label Swapping (AOLS) forms a key technology towards the implementation of All-Optical Packet Switching nodes (AOPS) for the future optical Internet. The capital expenditures of the deployment of AOLS increases with the size of the label spaces (i.e. the number of used labels), since a special optical device is needed for each recognized label on every node. Label space sizes are affected by the wayin which demands are routed. For instance, while shortest-path routing leads to the usage of fewer labels but high link utilization, minimum interference routing leads to the opposite. This project studies and proposes All-Optical Label Stacking (AOLStack), which is an extension of the AOLS architecture. AOLStack aims at reducing label spaces while easing the compromise with link utilization. In this project, an Integer Lineal Program is proposed with the objective of analyzing the softening of the aforementioned trade-off due to AOLStack. Furthermore, a heuristic aiming at finding good solutions in polynomial-time is proposed as well. Simulation results show that AOLStack either a) reduces the label spaces with a low increase in the link utilization or, similarly, b) uses better the residual bandwidth to decrease the number of labels even more.

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There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

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Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

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Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

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I prove that as long as we allow the marginal utility for money (lambda) to vary between purchases (similarly to the budget) then the quasi-linear and the ordinal budget-constrained models rationalize the same data. However, we know that lambda is approximately constant. I provide a simple constructive proof for the necessary and sufficient condition for the constant lambda rationalization, which I argue should replace the Generalized Axiom of Revealed Preference in empirical studies of consumer behavior. 'Go Cardinals!' It is the minimal requirement of any scientifi c theory that it is consistent with the data it is trying to explain. In the case of (Hicksian) consumer theory it was revealed preference -introduced by Samuelson (1938,1948) - that provided an empirical test to satisfy this need. At that time most of economic reasoning was done in terms of a competitive general equilibrium, a concept abstract enough so that it can be built on the ordinal preferences over baskets of goods - even if the extremely specialized ones of Arrow and Debreu. However, starting in the sixties, economics has moved beyond the 'invisible hand' explanation of how -even competitive- markets operate. A seemingly unavoidable step of this 'revolution' was that ever since, most economic research has been carried out in a partial equilibrium context. Now, the partial equilibrium approach does not mean that the rest of the markets are ignored, rather that they are held constant. In other words, there is a special commodity -call it money - that reflects the trade-offs of moving purchasing power across markets. As a result, the basic building block of consumer behavior in partial equilibrium is no longer the consumer's preferences over goods, rather her valuation of them, in terms of money. This new paradigm necessitates a new theory of revealed preference.

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In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.

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Background: Chronic mountain sickness (CMS), which is characterised by hypoxemia, erythrocytosis and pulmonary hypertension, is a major public health problem in high-altitude dwellers. The only existing treatment is descent to low altitude, an option that for social reasons almost never exists. Sleep disordered breathing may represent an underlying mechanism. We recently found that in mountaineers increasing the respiratory dead space markedly improves sleep disordered breathing. The aim of the present study was to assess the effects of this procedure on sleep disordered breathing in patients with CMS. Methods: In 10 male Bolivian high-altitude dwellers (mean ± SD age, 59 ± 9 y) suffering from CMS (haemoglobin >20 g/L) full night sleep recordings (Embletta, RespMed) were obtained in La Paz (3600 m). In random order, one night was spent with a 500 ml increase in dead space through a custom designed full face mask and the other night without it. Exclusion criteria were: secondary erythrocytosis, smoking, drug intake, acute infection, cardio- pulmonary or neurologic disease and travelling to low altitude in the preceding 6 months. Results: The major new finding was that added dead space dramatically improved sleep disordered breathing in patients suffering from CMS. The apnea/hypopnea index decreased by >50% (from 34.5 ± 25.0 to 16.8 ± 14.9, P = 0.003), the oxygen desaturation index decreased from 46.2 ± 23.0 to 27.2 ± 20.0 (P = 0.0004) and hypopnea index from 28.8 ± 20.9 to 16.3 ± 14.0 (P = 0.01), whereas nocturnal oxygen saturation increased from 79.8 ± 3.6 to 80.9 ± 3.0% (P = 0.009). The procedure was easily accepted and well tolerated. Conclusion: Here, we show for the very first time that an increase in respiratory dead space through a fitted mask dramatically improves nocturnal breathing in high-altitude dwellers suffering from CMS. We speculate that when used in the long-term, this procedure will improve erythrocytosis and pulmonary hypertension and offer an inexpensive and easily implementable treatment for this major public health problem.

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This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

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In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise which is white in time with some spatially homogeneous covariance. These estimates are obtained using tools of the Malliavin calculus. The most challenging part is the lower bound, which is obtained by adapting a general method developed by Kohatsu-Higa to the underlying spatially homogeneous Gaussian setting. Both lower and upper estimates have the same form: a Gaussian density with a variance which is equal to that of the mild solution of the corresponding linear equation with additive noise.

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The purpose of this study was to prospectively compare free-breathing navigator-gated cardiac-triggered three-dimensional steady-state free precession (SSFP) spin-labeling coronary magnetic resonance (MR) angiography performed by using Cartesian k-space sampling with that performed by using radial k-space sampling. A new dedicated placement of the two-dimensional selective labeling pulse and an individually adjusted labeling delay time approved by the institutional review board were used. In 14 volunteers (eight men, six women; mean age, 28.8 years) who gave informed consent, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel sharpness, vessel length, and subjective image quality were investigated. Differences between groups were analyzed with nonparametric tests (Wilcoxon, Pearson chi2). Radial imaging, as compared with Cartesian imaging, resulted in a significant reduction in the severity of motion artifacts, as well as an increase in SNR (26.9 vs 12.0, P < .05) in the coronary arteries and CNR (23.1 vs 8.8, P < .05) between the coronary arteries and the myocardium. A tendency toward improved vessel sharpness and vessel length was also found with radial imaging. Radial SSFP imaging is a promising technique for spin-labeling coronary MR angiography.

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We use store-specific data for a major UK supermarket chain to estimate the impact of planning on store output. Using the quasi-natural experiment of the variation in policies between England and other UK countries, we isolate the impact of Town Centre First policies. We find that space contributes directly to store productivity; and planning policies in England directly reduce output both by reducing store sizes and forcing stores onto less productive sites. We estimate that since the late 1980s planning policies have imposed a loss of output of at least 18.3 to 24.9% - more than a “lost decade’s” growth. JEL codes: D2, L51, L81, R32.

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The biosynthesis, intracellular transport, and surface expression of the beta cell glucose transporter GLUT2 was investigated in isolated islets and insulinoma cells. Using a trypsin sensitivity assay to measure cell surface expression, we determined that: (a) greater than 95% of GLUT2 was expressed on the plasma membrane; (b) GLUT2 did not recycle in intracellular vesicles; and (c) after trypsin treatment, reexpression of the intact transporter occurred with a t1/2 of approximately 7 h. Kinetics of intracellular transport of GLUT2 was investigated in pulse-labeling experiments combined with glycosidase treatment and the trypsin sensitivity assay. We determined that transport from the endoplasmic reticulum to the trans-Golgi network (TGN) occurred with a t1/2 of 15 min and that transport from the TGN to the plasma membrane required a similar half-time. When added at the start of a pulse-labeling experiment, brefeldin A prevented exit of GLUT2 from the endoplasmic reticulum. When the transporter was first accumulated in the TGN during a 15-min period of chase, but not following a low temperature (22 degrees C) incubation, addition of brefeldin A (BFA) prevented subsequent surface expression of the transporter. This indicated that brefeldin A prevented GLUT2 exit from the TGN by acting at a site proximal to the 22 degrees C block. Together, these data demonstrate that GLUT2 surface expression in beta cells is via the constitutive pathway, that transport can be blocked by BFA at two distinct steps and that once on the surface, GLUT2 does not recycle in intracellular vesicles.

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BACKGROUND: Isolated congenital atrioventricular block (CAVB) diagnosed in utero is associated with a high morbidity and mortality. Prognosis is especially poor when heart rate drops below 55 beats per minute (bpm) and when fetal hydrops develops. We describe the natural history and outcome of 24 infants with isolated CAVB diagnosed in utero, review the literature, and assess the risk factors that could predict outcome. METHODS: This was a retrospective multicenter study of 24 patients with isolated CAVB diagnosed in utero. RESULTS: CAVB was detected at a mean gestational age (GA) of 24.7 +/- 5.1 weeks. Ten fetuses initially presented with complete heart block. Low heart rate or incomplete heart block was the first documentation of bradyarrhythmia in the other 14 fetuses. In 11 of them, CAVB developed during pregnancy after a median time of 3 (range 1-16) weeks. Fetal hydrops developed in 10 of 24 (42%) fetuses at a mean GA of 27.6 +/- 5.1 weeks. Hydropic fetuses showed lower heart rates during pregnancy (47 +/- 10 bpm) than non-hydropic fetuses (57 +/- 10 bpm). There were three intrauterine deaths; all were hydropic and female. Nine viable females and 12 males were born at a mean GA of 37.1 +/- 6.1 weeks with an average birth weight of 3097 +/- 852 g. Fifteen CAVB patients required pacemaker (PM) intervention, 10 of them immediately after birth. Dilated cardiomyopathy (DCM) developed in three infants of whom two died of congestive heart failure, shortly after the diagnosis was made; one is still alive. Mortality before or after birth was 21%, and was associated with heart rates below 50 bpm and development of fetal hydrops. Poor outcome, defined as death, PM implantation, or development of DCM, occurred in 83% of cases and was associated with heart rates below 60 bpm during pregnancy. CONCLUSIONS: Isolated CAVB diagnosed in utero is associated with high morbidity and mortality. Patients who develop fetal hydrops show lower heart rates during pregnancy than patients who do not. A fetal heart rate below 50 bpm and development of fetal hydrops is associated with increased mortality. Rates below 60 bpm are associated with PM requirement and/or DCM.

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This article presents a new theory that separates the levels of communication and relates them circularly, namely, by separating time from space/meaning variables. Documenting this proposition requires sequential microdescriptions--a far-out project in the field of family therapy. In an extensive study of clinical and nonclinical families, starting with available microanalytic data on nonverbal parent-infant dialogue, distinct time organizations have been found to modify the degree of circularity between the levels of interaction according to the observed types of engagement, that is, consensual, conflictual, and paradoxical. The double description of the dyad as a totality versus the dyad as a framing/developing organization imparts crucial information on how development proceeds in dyadic, co-evolutive systems, and presumably in larger ones too. In this perspective, a model is elaborated and then applied to a case description in our therapeutic consultation.