Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Meta-analysis and imputation refines the association of 15q25 with smoking quantity.

Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

Authorship in scientific publications: analysis and recommendations.

In 2008, a Swiss Academies of Arts and Sciences working group chaired by Professor Emilio Bossi issued a "Memorandum on scientific integrity and the handling of misconduct in the scientific context", together with a paper setting out principles and procedures concerning integrity in scientific research. In the Memorandum, unjustified claims of authorship in scientific publications are referred to as a form of scientific misconduct - a view widely shared in other countries. In the Principles and Procedures, the main criteria for legitimate authorship are specified, as well as the associated responsibilities. It is in fact not uncommon for disputes about authorship to arise with regard to publications in fields where research is generally conducted by teams rather than individuals. Such disputes may concern not only the question who is or is not to be listed as an author but also, frequently, the precise sequence of names, if the list is to reflect the various authors' roles and contributions. Subjective assessments of the contributions made by the individual members of a research group may differ substantially. As scientific collaboration - often across national boundaries - is now increasingly common, ensuring appropriate recognition of all parties is a complex matter and, where disagreements arise, it may not be easy to reach a consensus. In addition, customs have changed over the past few decades; for example, the practice of granting "honorary" authorship to an eminent researcher - formerly not unusual - is no longer considered acceptable. It should be borne in mind that the publications list has become by far the most important indicator of a researcher's scientific performance; for this reason, appropriate authorship credit has become a decisive factor in the careers of young researchers, and it needs to be managed and protected accordingly. At the international and national level, certain practices have therefore developed concerning the listing of authors and the obligations of authorship. The Scientific Integrity Committee of the Swiss Academies of Arts and Sciences has collated the relevant principles and regulations and formulated recommendations for authorship in scientific publications. These should help to prevent authorship disputes and offer guidance in the event of conflicts.