Increased socioeconomic differences in mortality in eight Spanish provinces

In Spain, the study of socioeconomic differences in mortality has been limited by the fact that death certificates often do not include complete information on occupation. In this study, we chose those geographic areas with the highest quality information on occupation of the deceased in order to study socioeconomic differences in mortality from various causes of death. We used information from the death certificates of males who died between 30 and 64 years of age in eight Spanish provinces to compare mortality from the leading causes of death in professionals and managers (group I) and in manual laborers (group II) in 1980-82 and 1988-90. In each period the standardized mortality ratios (SMRs) were higher in group II, except for ischaemic heart disease during the first period, and cancer of the colon and rectum in both, although in the latter case the differences were not statistically significant. The ratio between the SMR from all causes in group II and group I was 1.27 in 1980-82, and 1.72 in 1988-90; for cancer of the colon and rectum the ratio went from 0.98 to 0.84, and for ischaemic heart disease, from 0.80 to 1.31. Except for cancer of the colon and rectum, which resulted in higher mortality in occupational group I, the excess mortality in occupational group II increased between the first and second period. The relation between socioeconomic level and mortality for ischaemic heart disease was reversed, a phenomenon similar to that which took place in the 1960s and 1970s in the developed countries.(ABSTRACT TRUNCATED AT 250 WORDS)     

Elastic behaviour of polyvinyl chloride melts

A study has been made of the elastic behaviour of Polyvinylchloride commercial samples at high shear stresses, under similar conditions to those used in the processing industry, by means of an extrusion capillary rheometer.The influence in the die swell of variables as molecular weight, temperature and shear rate has been studied. Results are in agreement with general literature data.Smooth extrudates are obtained only in the zone of intermediate shear rates. In this zone it is observed that the die swell increases with shear rate.     

Forecasting with unequally spaced data by a functional principal component approach

The Principal Component Regression model of multiple responses is extended to forccast a continuous-time stochastic process. Orthogonal projection on a subspace of trigonometric functions is applied in order to estimate the principal components using discrete-time observations from a sample of regular curves. The forecasts provided by this approach are compared with classical principal component regression on simulated data.     

Exciton storage by Mn(2+) in colloidal Mn(2+)-doped CdSe quantum dots

Colloidal Mn (2+)-doped CdSe quantum dots showing long excitonic photoluminescence decay times of up to tau exc = 15 mus at temperatures over 100 K are described. These decay times exceed those of undoped CdSe quantum dots by approximately 10 (3) and are shown to arise from the creation of excitons by back energy transfer from excited Mn (2+) dopant ions. A kinetic model describing thermal equilibrium between Mn (2+ 4)T 1 and CdSe excitonic excited states reproduces the experimental observations and reveals that, for some quantum dots, excitons can emit with near unity probability despite being approximately 100 meV above the Mn (2+ 4)T 1 state. The effect of Mn (2+) doping on CdSe quantum dot luminescence at high temperatures is thus completely opposite from that at low temperatures described previously.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.