49 resultados para cirrosi,ecografia,DCE-US,misurazione HVPG,progetto CLEVER

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Els anuncis televisius –i els mitjans publicitaris en general– tenen entre els seus propòsits els de captar l’atenció dels espectadors i arribar a una audiència de consumidors potencials. Aquestes dues finalitats no acostumen a representar processos separats o nivells de percepció diferents per part de l’espectador: si l’anunci assoleix la seva meta, despertarà un interès que serà l’interès d’aquells que es considera que tenen més probabilitats de comprar el producte o de realitzar l’acció que l’anunci vol promoure. Com més gran sigui la precisió a l’hora d’establir contacte amb aquestes persones, més específic, directe i, en conseqüència, reeixit, serà l’efecte del missatge. Pot semblar una paradoxa el fet que un dels procediments utilitzats per a atraure l’atenció de l’audiència sigui presentar un anunci el significat del qual no s’entén a primera vista. Però es tracta d’un recurs útil. La percepció d’alguns anuncis és semblant a la que es produeix al llegir poemes o certs relats curts, tenim la tendència a rellegir-los. Potser en una primera lectura no acabem de copsar-ne el significat, però això mateix es converteix en un repte que ens porta a llegir-lo una i altra vegada fins que descobrim el missatge del text. Quan arribem a aquest punt, l’esforç esdevé plaer estètic i el filtre que selecciona l’audiència també serveix per a seleccionar el client potencial.

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We present a Search and Matching model with heterogeneous workers (entrants and incumbents) that replicates the stylized facts characterizing the US and the Spanish labor markets. Under this benchmark, we find the Post-Match Labor Turnover Costs (PMLTC) to be the centerpiece to explain why the Spanish labor market is as volatile as the US one. The two driving forces governing this volatility are the gaps between entrants and incumbents in terms of separation costs and productivity. We use the model to analyze the cyclical implications of changes in labor market institutions affecting these two gaps. The scenario with a low degree of workers’ heterogeneity illustrates its suitability to understand why the Spanish labor market has become as volatile as the US one.

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This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

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This article provides a fresh methodological and empirical approach for assessing price level convergence and its relation to purchasing power parity (PPP) using annual price data for seventeen US cities. We suggest a new procedure that can handle a wide range of PPP concepts in the presence of multiple structural breaks using all possible pairs of real exchange rates. To deal with cross-sectional dependence, we use both cross-sectional demeaned data and a parametric bootstrap approach. In general, we find more evidence for stationarity when the parity restriction is not imposed, while imposing parity restriction provides leads toward the rejection of the panel stationar- ity. Our results can be embedded on the view of the Balassa-Samuelson approach, but where the slope of the time trend is allowed to change in the long-run. The median half-life point estimate are found to be lower than the consensus view regardless of the parity restriction.

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In this paper we examine the out-of-sample forecast performance of high-yield credit spreads regarding real-time and revised data on employment and industrial production in the US. We evaluate models using both a point forecast and a probability forecast exercise. Our main findings suggest the use of few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. This can be justified by observing that, especially for employment, there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks, such as an AR, and ARDL models that use either the term spread or the aggregate high-yield spread as exogenous regressor. Moreover, forecasts based on real-time data are generally comparable to forecasts based on revised data. JEL Classification: C22; C53; E32 Keywords: Credit spreads; Principal components; Forecasting; Real-time data.

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This paper uses sequential stochastic dominance procedures to compare the joint distribution of health and income across space and time. It is the First application of which we are aware of methods to compare multidimensional distributions of income and health using procedures that are robust to aggregation techniques. The paper's approach is more general than comparisons of health gradients and does not require the estimation of health equivalent incomes. We illustrate the approach by contrasting Canada and the US using comparable data. Canada dominates the US over the lower bidimensional welfare distribution of health and income, though not generally in terms of the uni-dimensional distribution of health or income. The paper also finds that welfare for both Canadians and Americans has not unambiguously improved during the last decade over the joint distribution of income and health, in spite of the fact that the uni-dimensional distributions of income have clearly improved during that period.

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The article investigates the private governance of financial markets by looking at the evolution of the regulatory debate on hedge funds in the US market. It starts from the premise that the privatization of regulation is always the result of a political decision and analyzes how this decision came about and was implemented in the case of hedge funds. The starting point is the failure of two initiatives on hedge funds that US regulators launched between 1999 an 2004, which the analysis explains by elaborating the concept of self-capture. Facing a trade off between the need to tackle publicly demonized issues and the difficulty of monitoring increasingly sophisticated and powerful private markets, regulators purposefully designed initiatives that were not meant to succeed, that is, they “self-captured” their own activity. By formulating initiatives that were inherently flawed, regulators saved their public role and at the same time paved the way for the privatization of hedge fund regulation. This explanation identifies a link between the failure of public initiatives and the success of private ones. It illustrates a specific case of formation of private authority in financial markets that points to a more general practice emerging in the regulation of finance.

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L’ artrosi de genoll es una de les malalties reumatològiques mes freqüents a l’Atenció Primària Objectiu. Prevalença de sinovitis Material i mètodes. Estudi transversal descriptiu. Resultats. 19 pacients, promig d’edat de 59,8 anys . L’estudi ecogràfic es va trobar vessament articular en 17 pacients (89.4%) i hipertrofia sinovial en 10 (52,6%) . Entre pacients amb i sense vessament existeixen diferencies significatives en el temps d’evolució i el qüestionari Lequesne. Conclusions. L’ecografia articular és una eina eficaç. La malaltia artròsica no es un procés purament degeneratiu, sinó que existeixen signes inflamatoris.

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The automatic diagnostic discrimination is an application of artificial intelligence techniques that can solve clinical cases based on imaging. Diffuse liver diseases are diseases of wide prominence in the population and insidious course, yet early in its progression. Early and effective diagnosis is necessary because many of these diseases progress to cirrhosis and liver cancer. The usual technique of choice for accurate diagnosis is liver biopsy, an invasive and not without incompatibilities one. It is proposed in this project an alternative non-invasive and free of contraindications method based on liver ultrasonography. The images are digitized and then analyzed using statistical techniques and analysis of texture. The results are validated from the pathology report. Finally, we apply artificial intelligence techniques as Fuzzy k-Means or Support Vector Machines and compare its significance to the analysis Statistics and the report of the clinician. The results show that this technique is significantly valid and a promising alternative as a noninvasive diagnostic chronic liver disease from diffuse involvement. Artificial Intelligence classifying techniques significantly improve the diagnosing discrimination compared to other statistics.

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The low levels of unemployment recorded in the UK in recent years are widely cited asevidence of the country’s improved economic performance, and the apparent convergence of unemployment rates across the country’s regions used to suggest that the longstanding divide in living standards between the relatively prosperous ‘south’ and the more depressed ‘north’ has been substantially narrowed. Dissenters from theseconclusions have drawn attention to the greatly increased extent of non-employment(around a quarter of the UK’s working age population are not in employment) and themarked regional dimension in its distribution across the country. Amongst these dissenters it is generally agreed that non-employment is concentrated amongst oldermales previously employed in the now very much smaller ‘heavy’ industries (e.g. coal,steel, shipbuilding).This paper uses the tools of compositiona l data analysis to provide a much richer picture of non-employment and one which challenges the conventional analysis wisdom about UK labour market performance as well as the dissenters view of the nature of theproblem. It is shown that, associated with the striking ‘north/south’ divide in nonemployment rates, there is a statistically significant relationship between the size of the non-employment rate and the composition of non-employment. Specifically, it is shown that the share of unemployment in non-employment is negatively correlated with the overall non-employment rate: in regions where the non-employment rate is high the share of unemployment is relatively low. So the unemployment rate is not a very reliable indicator of regional disparities in labour market performance. Even more importantly from a policy viewpoint, a significant positive relationship is found between the size ofthe non-employment rate and the share of those not employed through reason of sicknessor disability and it seems (contrary to the dissenters) that this connection is just as strong for women as it is for men

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Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

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Time scale parametric spike train distances like the Victor and the van Rossum distancesare often applied to study the neural code based on neural stimuli discrimination.Different neural coding hypotheses, such as rate or coincidence coding,can be assessed by combining a time scale parametric spike train distance with aclassifier in order to obtain the optimal discrimination performance. The time scalefor which the responses to different stimuli are distinguished best is assumed to bethe discriminative precision of the neural code. The relevance of temporal codingis evaluated by comparing the optimal discrimination performance with the oneachieved when assuming a rate code.We here characterize the measures quantifying the discrimination performance,the discriminative precision, and the relevance of temporal coding. Furthermore,we evaluate the information these quantities provide about the neural code. Weshow that the discriminative precision is too unspecific to be interpreted in termsof the time scales relevant for encoding. Accordingly, the time scale parametricnature of the distances is mainly an advantage because it allows maximizing thediscrimination performance across a whole set of measures with different sensitivitiesdetermined by the time scale parameter, but not due to the possibility toexamine the temporal properties of the neural code.

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With each passing election, U.S. political campaigns have renewed their efforts in courting the “Latino vote,” yet the Latino population is not a culturally homogenous voting bloc. This study examined how cultural identifications and acculturation attitudes in U.S. born Mexican Americans interacted with socioeconomic status (SES) to predict political orientation. Individuals who held stronger Mexican identity and supported biculturalism as an acculturation strategy had a more liberal orientation, while belonging to a higher SES group and holding stronger assimilation attitudes predicted a less liberal orientation. Mexican cultural identification interacted with SES such that those who held a weaker Mexican identity, but came from a higher social class were less liberal and more moderate in their political orientation. Weak Mexican identification and higher SES also predicted weaker endorsement of bicultural acculturation attitudes, which in turn, mediated the differences in political orientation. The acceptance of one’s ethnic identity and endorsement of bicultural attitudes predicted a more liberal political orientation. In light of these findings, political candidates should be cautious in how they pander to Latino constituents—referencing the groups’ ethnic culture or customs may distance constituents who are not strongly identified with their ethnic culture.

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This paper investigates the relationship between time variations in output and inflation dynamics and monetary policy in the US. There are changes in the structural coefficients and in the variance of the structural shocks. The policy rules in the 1970s and 1990s are similar as is the transmission of policy disturbances. Inflation persistence is only partly a monetary phenomena. Variations in the systematic component of policy have limited effects on the dynamics of output and inflation. Results are robust to alterations in the auxiliary assumptions.

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This paper investigates the relationship between monetary policy and the changes experienced by the US economy using a small scale New-Keynesian model. The model is estimated with Bayesian techniques and the stability of policy parameter estimates and of the transmission of policy shocks examined. The model fits well the data and produces forecasts comparable or superior to those of alternative specifications. The parameters of the policy rule, the variance and the transmission of policy shocks have been remarkably stable. The parameters of the Phillips curve and of the Euler equations are varying.