Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Profitability, uncertainty and multi-product firm product proliferation: The Spanish car industry

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market. Keywords: Product introduction, entry, uncertainty, multiproduct firms, automobile JEL codes: L11, L13

Environmental Tax on Products and Services Based on Their Carbon Footprint: A Case Study of the Pulp and Paper Sector

The main aim of this work is to define an environmental tax on products and services based on their carbon footprint. We examine the relevance of conventional life cycle analysis (LCA) and environmentally extended input-output analysis (EIO) as methodological tools to identify emission intensities of products and services on which the tax is based. The short-term price effects of the tax and the policy implications of considering non-GHG are also analyzed. The results from the specific case study on pulp production show that the environmental tax rate based on the LCA approach (1,8%) is higher than both EIO approaches (0,8% for product and 1,4% for industry approach), but they are comparable. Even though LCA is more product specific and provides detailed analysis, EIO would be the more relevant approach to apply economy wide environmental tax. When the environmental tax considers non-GHG emissions instead of only CO2, sectors such as agriculture, mining of coal and extraction of peat, and food exhibit higher environmental tax and price effects. Therefore, it is worthwhile for policy makers to pay attention on the implication of considering only CO2 tax or GHG emissions tax in order for such a policy measure to be effective and meaningful. Keywords: Environmental tax; Life cycle analysis; Environmental input-output analysis.

Cinéma, machine à mondes : essai sur les films à univers multiples

Dans cet ouvrage, l'auteur propose une conceptualisation théorique de la coprésence en un même film de mondes multiples en abordant différents paramètres (hétérogénéité de la facture de l'image, pratiques du montage alterné, typologie des enchâssements, expansion sérielle, etc.) sur la base d'un corpus de films de fiction récents qui appartiennent pour la plupart au genre de la science-fiction (Matrix, Dark City, Avalon, Resident Evil, Avatar,...). Issue de la filmologie, la notion de « diégèse » y est développée à la fois dans le potentiel d'autonomisation dont témoigne la conception mondaine qui semble dominer aujourd'hui à l'ère des jeux vidéo, dans ses liens avec le récit et dans une perspective intermédiale. Les films discutés ont la particularité de mettre en scène des machines permettant aux personnages de passer d'un monde à l'autre : les modes de figuration de ces technologies sont investigués en lien avec les imaginaires du dispositif cinématographique et les potentialité du montage. La comparaison entre les films (Tron et son récent sequel, Totall Recall et son remake) et entre des oeuvres filmiques et littéraires (en particulier les nouvelles de Philip K. Dick et Simlacron 3 de Galouye) constitue un outil d'analyse permettant de saisir la contemporanéité de cette problématique, envisagée sur le plan esthétique dans le contexte de l'imagerie numérique.

Gene expression databases and data mining.

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.

Report of the Working Group on Sports Sponsorship by the Alcohol Industry

Report of the Working Group on Sports Sponsorship by the Alcohol Industry Click here to download PDF 60KB

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

The tobacco industry's past role in weight control related to smoking.

BACKGROUND: Smoking is thought to produce an appetite-suppressing effect by many smokers. Thus, the fear of body weight gain often outweighs the perception of health benefits associated with smoking cessation, particularly in adolescents. We examined whether the tobacco industry played a role in appetite and body weight control related to smoking and smoking cessation. METHODS: We performed a systematic search within the archives of six major US and UK tobacco companies (American Tobacco, Philip Morris, RJ Reynolds, Lorillard, Brown & Williamson and British American Tobacco) that were Defendants in tobacco litigation settled in 1998. Findings are dated from 1949 to 1999. RESULTS: The documents revealed the strategies planned and used by the industry to enhance effects of smoking on weight and appetite, mostly by chemical modifications of cigarettes contents. Appetite-suppressant molecules, such as tartaric acid and 2-acetylpyridine were added to some cigarettes. CONCLUSION: These tobacco companies played an active and not disclaimed role in the anti-appetite effects of smoking, at least in the past, by adding appetite-suppressant molecules into their cigarettes.

The tobacco industry's past role in weight control related to smoking

Résumé (français)ContexteLe tabagisme est connu pour produire un effet coupe-faim chez la plupart des fumeurs. La crainte de la prise de poids à l'arrêt de la cigarette l'emporte souvent sur la perception des bénéfices sur la santé associés à l'abandon du tabac, particulièrement chez les adolescents. Nous avons examiné quel a été le rôle de l'industrie du tabac dans cet effet de la fumée sur l'appétit et sur le contrôle du poids.MéthodesNous avons réalisé une recherche systématique dans les archives de six grandes compagnies de tabac américaines et du Royaume-Uni (American Tobacco, Philip Morris, RJ Reynolds, Lorillard, Brown & Williamson et British American Tobacco) qui avaient été mises en cause dans les procès du tabac en 1998 aux Etats-Unis. Les résultats concernent les années 1949 à 1999.RésultatsLes archives de ces industries montrent qu'elles ont mis au point et ont utilisé diverses stratégies pour améliorer les effets du tabagisme sur le poids et l'appétit, la plupart du temps en réalisant des modifications chimiques des cigarettes. Des substances coupe-faim, telles que l'acide tartrique et le 2-acétylpyridine ont notamment été ajoutées aux cigarettes.ConclusionEn tout cas par le passé, ces compagnies de tabac ont activement modifié leurs cigarettes afin d'en augmenter l'effet de diminution de l'appétit, notamment en y ajoutant des substances coupe-faim.

Love machine

This poster provides advice on the use of condoms as a method of protection from unplanned pregnancy and sexually transmitted infections (STIs). It also provides contact details for the�Genito Urinary Medicine (GUM) clinics in Northern Ireland.

How can industry engage with the NICRN?

The Northern Ireland Clinical Research Network (NICRN) undertakes research in a range of medical fields. The NICRN is part of a UK-wide initiative to provide opportunities for patients and clinicians to participate in high-quality clinical research. This leaflet is targeted towards commercial partners who may wish to conduct clinical trials within Health and Social Care (HSC). The NICRN offers a range of supports for commercial partners, which allow clinical trials to get underway quickly and ensure they run smoothly.� Increasing opportunities for HSC service users to participate in clinical research and trials has the potential to bring benefits for the patients themselves and longer-term benefits to the HSC system in Northern Ireland as a whole.