977 resultados para analytical approaches
Resumo:
In recent years, some epidemiologic studies have attributed adverse effects of air pollutants on health not only to particles and sulfur dioxide but also to photochemical air pollutants (nitrogen dioxide and ozone). The effects are usually small, leading to some inconsistencies in the results of the studies. Furthermore, the different methodologic approaches of the studies used has made it difficult to derive generic conclusions. We provide here a quantitative summary of the short-term effects of photochemical air pollutants on mortality in seven Spanish cities involved in the EMECAM project, using generalized additive models from analyses of single and multiple pollutants. Nitrogen dioxide and ozone data were provided by seven EMECAM cities (Barcelona, Gijón, Huelva, Madrid, Oviedo, Seville, and Valencia). Mortality indicators included daily total mortality from all causes excluding external causes, daily cardiovascular mortality, and daily respiratory mortality. Individual estimates, obtained from city-specific generalized additive Poisson autoregressive models, were combined by means of fixed effects models and, if significant heterogeneity among local estimates was found, also by random effects models. Significant positive associations were found between daily mortality (all causes and cardiovascular) and NO(2), once the rest of air pollutants were taken into account. A 10 microg/m(3) increase in the 24-hr average 1-day NO(2)level was associated with an increase in the daily number of deaths of 0.43% [95% confidence interval (CI), -0.003-0.86%] for all causes excluding external. In the case of significant relationships, relative risks for cause-specific mortality were nearly twice as much as that for total mortality for all the photochemical pollutants. Ozone was independently related only to cardiovascular daily mortality. No independent statistically significant relationship between photochemical air pollutants and respiratory mortality was found. The results in this study suggest that, given the present levels of photochemical pollutants, people living in Spanish cities are exposed to health risks derived from air pollution.
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We put together the different conceptual issues involved in measuring inequality of opportunity, discuss how these concepts have been translated into computable measures, and point out the problems and choices researchers face when implementing these measures. Our analysis identifies and suggests several new possibilities to measure inequality of opportunity. The approaches are illustrated with a selective survey of the empirical literature on income inequality of opportunity.
Resumo:
In recent years, a growing number of studies suggests that increases in air pollution levels may have short-term impact on human health, even at pollution levels similar to or lower than those which have been considered to be safe to date. The different methodological approaches and the varying analysis techniques employed have made it difficult to make a direct comparison among all of the findings, preventing any clear conclusions from being drawn. This has led to multicenter projects such as the APHEA (Short-Term Impact of Air Pollution on Health. A European Approach) within a European Scope. The EMECAM Project falls within the context of the aforesaid multicenter studies and has a wide-ranging projection nationwide within Spain. Fourteen (14) cities throughout Spain were included in this Project (Barcelona, Metropolitan Area of Bilbao, Cartagena, Castellón, Gijón, Huelva, Madrid, Pamplona, Seville, Oviedo, Valencia, Vigo, Vitoria and Saragossa) representing different sociodemographic, climate and environmental situations, adding up to a total of nearly nine million inhabitants. The objective of the EMECAM project is that to asses the short-term impact of air pollution throughout all of the participating cities on the mortality for all causes, on the population and on individuals over age 70, for respiratory and cardiovascular design causes. For this purpose, with an ecological, the time series data analyzed taking the daily deaths, pollutants, temperature data and other factors taken from records kept by public institutions. The period of time throughout which this study was conducted, although not exactly the same for all of the cities involved, runs in all cases from 1990 to 1996. The degree of relationship measured by means of an autoregressive Poisson regression. In the future, the results of each city will be combined by means of a meta-analysis.
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The impact of the adequacy of empirical therapy on outcome for patients with bloodstream infections (BSI) is key for determining whether adequate empirical coverage should be prioritized over other, more conservative approaches. Recent systematic reviews outlined the need for new studies in the field, using improved methodologies. We assessed the impact of inadequate empirical treatment on the mortality of patients with BSI in the present-day context, incorporating recent methodological recommendations. A prospective multicenter cohort including all BSI episodes in adult patients was performed in 15 hospitals in Andalucía, Spain, over a 2-month period in 2006 to 2007. The main outcome variables were 14- and 30-day mortality. Adjusted analyses were performed by multivariate analysis and propensity score-based matching. Eight hundred one episodes were included. Inadequate empirical therapy was administered in 199 (24.8%) episodes; mortality at days 14 and 30 was 18.55% and 22.6%, respectively. After controlling for age, Charlson index, Pitt score, neutropenia, source, etiology, and presentation with severe sepsis or shock, inadequate empirical treatment was associated with increased mortality at days 14 and 30 (odds ratios [ORs], 2.12 and 1.56; 95% confidence intervals [95% CI], 1.34 to 3.34 and 1.01 to 2.40, respectively). The adjusted ORs after a propensity score-based matched analysis were 3.03 and 1.70 (95% CI, 1.60 to 5.74 and 0.98 to 2.98, respectively). In conclusion, inadequate empirical therapy is independently associated with increased mortality in patients with BSI. Programs to improve the quality of empirical therapy in patients with suspicion of BSI and optimization of definitive therapy should be implemented.
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Descriptive epidemiology research involves collecting data from large numbers of subjects. Obtaining these data requires approaches designed to achieve maximum participation or response rates among respondents possessing the desired information. We analyze participation and response rates in a population-based epidemiological study though a telephone survey and identify factors implicated in consenting to participate. Rates found exceeded those reported in the literature and they were higher for afternoon calls than for morning calls. Women and subjects older than 40 years were the most likely to answer the telephone. The study identified geographical differences, with higher RRs in districts in southern Spain that are not considered urbanized. This information may be helpful for designing more efficient community epidemiology projects.
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High-resolution tomographic imaging of the shallow subsurface is becoming increasingly important for a wide range of environmental, hydrological and engineering applications. Because of their superior resolution power, their sensitivity to pertinent petrophysical parameters, and their far reaching complementarities, both seismic and georadar crosshole imaging are of particular importance. To date, corresponding approaches have largely relied on asymptotic, ray-based approaches, which only account for a very small part of the observed wavefields, inherently suffer from a limited resolution, and in complex environments may prove to be inadequate. These problems can potentially be alleviated through waveform inversion. We have developed an acoustic waveform inversion approach for crosshole seismic data whose kernel is based on a finite-difference time-domain (FDTD) solution of the 2-D acoustic wave equations. This algorithm is tested on and applied to synthetic data from seismic velocity models of increasing complexity and realism and the results are compared to those obtained using state-of-the-art ray-based traveltime tomography. Regardless of the heterogeneity of the underlying models, the waveform inversion approach has the potential of reliably resolving both the geometry and the acoustic properties of features of the size of less than half a dominant wavelength. Our results do, however, also indicate that, within their inherent resolution limits, ray-based approaches provide an effective and efficient means to obtain satisfactory tomographic reconstructions of the seismic velocity structure in the presence of mild to moderate heterogeneity and in absence of strong scattering. Conversely, the excess effort of waveform inversion provides the greatest benefits for the most heterogeneous, and arguably most realistic, environments where multiple scattering effects tend to be prevalent and ray-based methods lose most of their effectiveness.
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We derive analytical expressions for the propagation speed of downward combustion fronts of thin solid fuels with a background flow initially at rest. The classical combustion model for thin solid fuels that consists of five coupled reaction-convection-diffusion equations is here reduced into a single equation with the gas temperature as the single variable. For doing so we apply a two-zone combustion model that divides the system into a preheating region and a pyrolyzing region. The speed of the combustion front is obtained after matching the temperature and its derivative at the location that separates both regions.We also derive a simplified version of this analytical expression expected to be valid for a wide range of cases. Flame front velocities predicted by our analyticalexpressions agree well with experimental data found in the literature for a large variety of cases and substantially improve the results obtained from a previous well-known analytical expression
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MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.
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Pathogen inactivation of blood products represents a global and major paradigm shift in transfusion medicine. In the next near future, it is likely that most blood products will be inactivated by various physicochemical approaches. The concept of blood safety will be challenged as well as transfusion medicine practice, notably for donor selection or biological qualification. In this context, it seems mandatory to develop analytical economic approaches by assessing costs-benefits ratio of blood transfusion as well as to set up cohorts of patients based on hemovigilance networks allowing rigorous scientific analysis of the benefits and the risks of blood transfusion at short- and long-term.
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For the last decade Europe has perceived itself to be under a constant threat from jihadistinspired terrorism. Terrorist organizations motivated by other ideologies are still active throughout the European Union, but the 2010 Europol annual report clearly states that “Islamist terrorism is still perceived as the biggest threat to most Member States,” and statements from the highest-ranking officials in most European countries confirm this observation (EUROPOL, 2010, p. 6). Authorities base their assessment on the extensive intelligence and investigative activities directed against jihadist networks taking place in virtually every European country. On average, in fact, European authorities arrest some 200 individuals and thwart a handful of plots of jihadist inspiration every year (EUROPOL, 2009). Keeping the global scenario in mind, European authorities deem this dynamic likely to continue in the foreseeable future.
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A model-based approach for fault diagnosis is proposed, where the fault detection is based on checking the consistencyof the Analytical Redundancy Relations (ARRs) using an interval tool. The tool takes into account the uncertainty in theparameters and the measurements using intervals. Faults are explicitly included in the model, which allows for the exploitation of additional information. This information is obtained from partial derivatives computed from the ARRs. The signs in the residuals are used to prune the candidate space when performing the fault diagnosis task. The method is illustrated using a two-tank example, in which these aspects are shown to have an impact on the diagnosis and fault discrimination, since the proposed method goes beyond the structural methods
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Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.