846 resultados para Real Interest Rate Differentials


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Exchange rates are important macroeconomic prices and changes in these rates a ect economic activity, prices, interest rates, and trade ows. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that the global vector autoregressions model (GVAR) proposed by Pesaran and co-authors can add relevant information to the literature on measuring exchange rate misalignment. Our empirical exercise suggests that the estimate exchange rate misalignment obtained from GVAR can be quite di erent to that using the traditional cointegrated time series techniques, which treat countries as detached entities. The di erences between the two approaches are more pronounced for small and developing countries. Our results also suggest a strong interdependence among eurozone countries, as expected

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An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine's capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine's potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

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Background: Tolerance and response to antiviral HCV treatment is poor in advanced fibrosis. The aim of this study was to assess SVR rate and its predictive factors in HCV advanced fibrosis patients treated in real life with full dose PEG-IFN plus RBV and to evaluate the adverse events related to treatment. Methods: A multicentric, retrospective study was conducted at six university hospitals. METAVIR F3 and F4 HCV monoinfected patients who were treated with PEG-IFN and RBV had their data analyzed. A stepwise logistic regression analysis was performed to identify the variables independently related to SVR. Adverse events were recorded during treatment. Results: 308 patients were included, 75% genotype 1 and 23% genotype 3. METAVIR F3 was present in 39% and F4 in 61% of patients. The median Child Pugh score for F4 patients was 5 (5–9). The global SVR rate was 34%, 11% were relapsers and 55% were nonresponders. SVR rates were similar between patients treated with PEG-IFN alfa 2a or alfa 2b (p = 0.24). SVR rates according to Child–Pugh score were 26% (Child A) and 18% (Child B). The independent factors related to SVR in F4 patients were genotype 3, RVR and fewer Child Pugh score points. Treatment interruption occurred in 31% patients and death occurred in 1.9%, all with liver cirrhosis. Conclusion: Treatment of HCV in patients with advanced fibrosis should not be postponed. However, a very careful evaluation of cirrhotic patients must be performed before treatment is indicated and careful monitoring is required during treatment.

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The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.

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Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

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In recent decades, Organic Thin Film Transistors (OTFTs) have attracted lots of interest due to their low cost, large area and flexible properties which have brought them to be considered the building blocks of the future organic electronics. Experimentally, devices based on the same organic material deposited in different ways, i.e. by varying the deposition rate of the molecules, show different electrical performance. As predicted theoretically, this is due to the speed and rate by which charge carriers can be transported by hopping in organic thin films, transport that depends on the molecular arrangement of the molecules. This strongly suggests a correlation between the morphology of the organic semiconductor and the performance of the OTFT and hence motivated us to carry out an in-situ real time SPM study of organic semiconductor growth as an almost unprecedent experiment with the aim to fully describe the morphological evolution of the ultra-thin film and find the relevant morphological parameters affecting the OTFT electrical response. For the case of 6T on silicon oxide, we have shown that the growth mechanism is 2D+3D, with a roughening transition at the third layer and a rapid roughening. Relevant morphological parameters have been extracted by the AFM images. We also developed an original mathematical model to estimate theoretically and more accurately than before, the capacitance of an EFM tip in front of a metallic substrate. Finally, we obtained Ultra High Vacuum (UHV) AFM images of 6T at lying molecules layer both on silicon oxide and on top of 6T islands. Moreover, we performed ex-situ AFM imaging on a bilayer film composed of pentacene (a p-type semiconductor) and C60 (an n-type semiconductor).

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This study investigated the use of real-world contexts during instruction in a high school physics class - through building file folder bridges- and the resulting effect upon student interest in the subject matter, level of understanding, and degree of retention. In particular, the study focused upon whether increases in student interest were attained through the use of real-world contexts, and if the elevated interest level led to a higher degree of subject matter understanding than would be achieved using more traditional teaching methods. The study also determined whether using real-world contexts ultimately resulted in achievement of greater levels of knowledge retention by students. Class observations during traditionally taught units and during units that incorporated real-world contexts, along with a post-graduation questionnaire, were used to assess differences in student interest levels. Student pre- and post-unit test scores were evaluated and compared to determine if statistical differences existed in levels of understanding resulting from the different teaching methods. The post-graduation questionnaire results provided evidence of retention that could be related back to teaching methods. The results of this study revealed the importance of incorporating real-world contexts into science and mathematics courses. Students better understood the relevance of the lessons, which led to higher levels of interest and greater understanding than was achieved through more traditional teaching methods. The use of real-world contexts improved knowledge retention.