‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling

The aim of the present study was to examine further the role that self-identity plays in the theory of planned behaviour and, more specifically, to: (1) examine the combined effects of self-identity and social identity constructs on intention and behaviour, and (2) examine the effects of self-identity as a function of past experience of performing the behaviour. The study was concerned with the prediction of intention to engage in household recycling and reported recycling behaviour. A sample of 143 community residents participated in the study. It was prospective in design: measures of the predictors and intention were obtained at the first wave of data collection, whereas behaviour was assessed two weeks later. Selfidentity significantly predicted behavioural intention, a relationship that was not dependent on the extent to which the behaviour had been performed in the past. As expected, there was also evidence that the perceived norm of a behaviourally relevant reference group was related to behavioural intention, but only for participants who identified strongly with the group, whereas the relationship between perceived behavioural control (a personal factor) and intention was strongest for low identifiers.

The theory of planned behaviour: Self identity, social identity, and group norms

In this landmark book, Scott Page redefines the way we understand ourselves in relation to one another. The Difference is about how we think in groups--and how our collective wisdom exceeds the sum of its parts. Why can teams of people find better solutions than brilliant individuals working alone? And why are the best group decisions and predictions those that draw upon the very qualities that make each of us unique? The answers lie in diversity--not what we look like outside, but what we look like within, our distinct tools and abilities. The Difference reveals that progress and innovation may depend less on lone thinkers with enormous IQs than on diverse people working together and capitalizing on their individuality. Page shows how groups that display a range of perspectives outperform groups of like-minded experts. Diversity yields superior outcomes, and Page proves it using his own cutting-edge research. Moving beyond the politics that cloud standard debates about diversity, he explains why difference beats out homogeneity, whether you're talking about citizens in a democracy or scientists in the laboratory. He examines practical ways to apply diversity's logic to a host of problems, and along the way offers fascinating and surprising examples, from the redesign of the Chicago "El" to the truth about where we store our ketchup. Page changes the way we understand diversity--how to harness its untapped potential, how to understand and avoid its traps, and how we can leverage our differences for the benefit of all.

Prologue to The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies

Aims Cardiovascular disease (CVD), together with its main components, coronary heart disease (CHD), and cerebrovascular diseases, is the main source of morbidity and mortality in the European Union (EU), but to date, there has not been any systematic cost-of-illness study to assess the economic impact of CVD in the EU.

Methods and results CVD-related expenditure was estimated using aggregate data on morbidity, mortality, and healthcare resource use. Healthcare costs were estimated from expenditure on primary, outpatient, emergency, and inpatient care, as well as medications. Costs of unpaid care and lost earnings due to morbidity and premature death were included in the study. CVD was estimated to cost the EU €169 billion annually, with healthcare accounting for 62% of costs. Productivity losses and informal care represented 21% and 17% of costs, respectively. CHD represented 27% and cerebrovascular diseases 20% of overall CVD costs.

Conclusion CVD is a leading public health problem. Our study is the first to assess the economic burden of CVD across the EU, and our results should help policy makers evaluate policy impact and prioritize research expenditures. However, because of data unavailability, our study has important limitations, which highlight the need for more accurate and comparable CVD-specific information.

Economic burden of cardiovascular diseases in the enlarged European Union.

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Partitioning European grassland net ecosystem CO2 exchange into gross primary productivity and ecosystem respiration using light response function analysis

Constance Berthier

Papers

Sixth framework programme

Deliverable n° D3.2 - RS 2b "Final set of sustainability criteria and indicator s for assessment of electricity supply options"