Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

The EPAGE internet guideline as a decision support tool for determining the appropriateness of colonoscopy

RÉSUMÉ Contexte : Peu d'études ont examiné la façon dont les médecins appréhendent les guidelines, et encore moins celle dont ils perçoivent de tels guidelines disponibles sur Internet. Cette étude évalue l'acceptation par les médecins d'un guideline électronique portant sur l'adéquation de la colonoscopie. Méthode : Des gastroentérologues participant à une étude observationnelle internationale ont consulté un guideline électronique pour une série consécutive de patients adressés pour une colonoscopie. Le guideline a été élaboré par le Panel Européen sur l'Adéquation de l'Endoscopie Gastro-intestinale (EPAGE en version anglaise), utilisant une méthode validée (RAND). Les opinions des médecins sur le guideline, sur le site Internet et sur les perspectives d'utilisation ont été recueillies au moyen de questionnaires. Résultats : 289 patients ont été inclus dans l'étude. Le temps moyen pour consulter le site Internet a été de 1.8 min et 86% des médecins l'ont considéré comme simple à utiliser. Les recommandations ont été facilement localisées pour 82% des patients et les médecins étaient d'accord avec l'adéquation de la colonoscopie dans 86% des cas. Selon les critères EPAGE, la colonoscopie était appropriée, incertaine et inappropriée, respectivement chez 59, 28 et 13% des patients. Conclusions : Le guideline EPAGE a été considéré comme acceptable et simple à utiliser. L'utilisation, l'utilité et la pertinence du site Internet a été jugée comme acceptable. Son utilisation effective dépendra cependant de la levée de certains obstacles au niveau organisationnel et culturel.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

The Relevance of the Principal-Agent Model for the Analysis of Public Policies : Do the Objectives Conflict ?

This paper aims to provide empirical support for the use of the principal-agent framework in the analysis of public sector and public policies. After reviewing the different conditions to be met for a relevant analysis of the relationship between population and government using the principal-agent theory, our paper focuses on the assumption of conflicting goals between the principal and the agent. A principal-agent analysis assumes in effect that inefficiencies may arise because principal and agent pursue different goals. Using data collected during an amalgamation project of two Swiss municipalities, we show the existence of a gap between the goals of the population and those of the government. Consequently, inefficiencies as predicted by the principal-agent model may arise during the implementation of a public policy, i.e. an amalgamation project. In a context of direct democracy where policies are regularly subjected to referendum, the conflict of objectives may even lead to a total failure of the policy at the polls.

Soins palliatifs et soins de support: à la frontière de la toute-puissance médicale [Palliative and supportive care: at the frontiers of medical omnipotence].

Cancer patients have physical, social, spiritual and emotional needs. They may suffer from severe physical symptoms, from social isolation, spiritual abandonment, and emotions such as sadness and anxiety, or feelings of deception, helplessness, anger and guilt. In some of them, the disease is rapidly progressing and ultimately they die. Their demanding care evokes intense feelings in health care providers, the more since these incurable patients represent a challenge, which could be condensed under the heading "the challenge of medical omnipotence". We suppose that the way health care providers cope with these circumstances has a profound influence on the way these patients are cared for. The attitudes towards the emerging heterogeneous movement of palliative and supportive care and towards its different models of implementation can be viewed from this point of view. We try to demonstrate these interrelations and to discuss the danger that may arise if they remain obscure and unreflected.

Prise en charge nutritionnelle préopératoire. [Preoperative nutritional support.]

Undernutrition is an independent factor of postoperative morbidity and mortality The aim of a preoperative nutritional support is to enhance immune muscular and cognitive functions, and to support wound healing This nutritional support (e g dietary management enteral or parenteral nutrition) should be limited to high risk situations with a beneficial effect of nutrition for the patient undernutrition major surgery and elderly Preoperative nutritional support should be scheduled for atleast 7 to 10 days before the surgery During the preoperative period the type and route of an eventual postoperative nutritional assistance should be anticipated In the case of emergency surgery nutritional assessment of the patient should be done as soon as possible before surgery or in the 48 h postoperative period Finally, in elective surgery, preoperative fasting should be limited to 2-3 hours for clear liquids and 6 hours for solids (C) 2010 Published by Elsevier Masson SAS

Support for Seasonal Influenza Vaccination Requirements among US Healthcare Personnel.

Objective. To measure support for seasonal influenza vaccination requirements among US healthcare personnel (HCP) and its associations with attitudes regarding influenza and influenza vaccination and self-reported coverage by existing vaccination requirements. Design. Between June 1 and June 30, 2010, we surveyed a sample of US HCP ([Formula: see text]) recruited using an existing probability-based online research panel of participants representing the US general population as a sampling frame. Setting. General community. Participants. Eligible HCP who (1) reported having worked as medical doctors, health technologists, healthcare support staff, or other health practitioners or who (2) reported having worked in hospitals, ambulatory care facilities, long-term care facilities, or other health-related settings. Methods. We analyzed support for seasonal influenza vaccination requirements for HCP using proportion estimation and multivariable probit models. Results. A total of 57.4% (95% confidence interval, 53.3%-61.5%) of US HCP agreed that HCP should be required to be vaccinated for seasonal influenza. Support for mandatory vaccination was statistically significantly higher among HCP who were subject to employer-based influenza vaccination requirements, who considered influenza to be a serious disease, and who agreed that influenza vaccine was safe and effective. Conclusions. A majority of HCP support influenza vaccination requirements. Moreover, providing HCP with information about the safety of influenza vaccination and communicating that immunization of HCP is a patient safety issue may be important for generating staff support for influenza vaccination requirements.