Cumulative energy demand has been used as a methodology to assess life cycle environmental impacts of commodity production since the early seventies, but has also been criticized because it focuses on energy only. During the past 30 years there has been much research into the development of more complex single-score life cycle impact assessment methodologies. However, a comprehensive analysis of potential similarities and differences between these methodologies and cumulative energy demand has not been carried out so far. Here we compare the cumulative energy demand of 498 commodities with the results of six frequently applied environmental life cycle impact assessment methodologies. Commodity groups included are metals, glass, paper and cardboard, organic and inorganic chemicals, agricultural products, construction materials, and plastics. We show that all impact assessment methods investigated often provide converging results, in spite of the different philosophies behind these methodologies. Fossil energy use is identified by all methodologies as the most important driver of environmental burden of the majority of the commodities included,with the main exception of agricultural products. We conclude that a wide range of life cycle environmental assessment methodologies point into the same environmental direction for the production of many commodities.

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This paper proposes nonparametric deconvolution density estimation over S 2 . Here we would think of the S 2 elements of interest being corrupted by random SO(3) elements (rotations). The resulting density on the observations would be a convolution of the SO(3) density with the true S 2 density. Consequently, the methodology, as in the Euclidean case, would be to use Fourier analysis on SO(3) and S 2 , involving rotational and spherical harmonics, respectively. We especially consider the case where the deconvolution operator is a bounded operator lowering the Sobolev order by a finite amount. Consistency results are obtained with rates of convergence calculated under the expected L 2 and Sobolev square norms that are proportionally inverse to some power of the sample size. As an example we introduce the rotational version of the Laplace distribution.1998 Academic Press

In dominant spinocerebellar ataxias (SCAs), the issue of whether non-CAG dependent factors contribute to onset age remains unsettled. Data on SCA genotype, onset age, normal/expanded CAG repeat length, sex of the patient and transmitting parent, and family details were available from 802 patients. Based on the model [log(10) (age at onset) = k - b CAG(exp) + epsilon], we examined changes in adjusted R(2) and residual standard error following incorporation of the other factors in this model. The expanded repeat explained 44.3 to 74.9% of onset age variance, although this was less than 50% in SCA3 and SCA6, implicating a large effect of non-CAG factors. The relation between onset age and CAG repeat was similar for SCA1, 3, 6, and 7, but different for SCA2, pointing to different polyglutamine effects in SCA2. For SCA2 and SCA3, 17.1 and 45.5% of onset age variance, respectively, were explained by currently (unidentified) familial factors. We found a significant contribution of the nonexpanded allele in SCA1 and SCA6. Besides polyglutamine motif (determined by the expanded CAG repeat length), we identified the following age at onset modifiers: protein context in SCA2; familial factors in SCA2 and SCA3; and the nonexpanded CAG repeat in SCA1 and SCA6.

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