A survey on algorithmic aspects of modular decomposition

The modular decomposition is a technique that applies but is not restricted to graphs. The notion of module naturally appears in the proofs of many graph theoretical theorems. Computing the modular decomposition tree is an important preprocessing step to solve a large number of combinatorial optimization problems. Since the first polynomial time algorithm in the early 70's, the algorithmic of the modular decomposition has known an important development. This paper survey the ideas and techniques that arose from this line of research

Usefulness of EQ-5D in Assessing Health Status in Primary Care Patients with Major Depressive Disorder

Objectives Major depressive disorder (MDD) is a prevalent psychiatric disorder associated with impaired patient functioning and reductions in health-related quality of life (HRQL). The present study describes the impact of MDD on patients' HRQL and examines preference-based health state differences by patient features and clinical characteristics. Methods 95 French primary care practitioners recruited 250 patients with a DSM-IV diagnosis of MDD for inclusion in an eight-week follow-up cohort. Patient assessments included the Montgomery Asberg Depression Rating Scale (MADRS), the Clinical Global Impression of Severity (CGI), the Short Form-36 Item scale (SF-36), the Quality of Life Depression Scale (QLDS) and the EuroQoL (EQ-5D). Results The mean EQ-5D utility at baseline was 0.33, and 8% of patients rated their health state as worse than death. There were no statistically significant differences in utilities by demographic features. Significant differences were found in mean utilities by level of disease severity assessed by CGI. The different clinical response profiles, assessed by MADRS, were also revealed by EQ-5D at endpoint: 0.85 for responders remitters, 0.72 for responders non-remitter, and 0.58 for non-responders. Even if HRQL and EQ-5D were moderately correlated, they shared only 40% of variance between baseline and endpoint. Conclusions Self-reported patient valuations for depression are important patient-reported outcomes for cost-effectiveness evaluations of new antidepressant compounds and help in further understanding patient compliance with antidepressant treatment

Risk attitude, beliefs updating and the information content of trades: an experiment

In this paper, the authors conduct a series of experiments that simulate trading in financial markets and which allows them to identify the different effects that subjects’ risk attitudes and belief updating rules have on the information content of the order flow. They find that there are very few risk-neutral subjects and that subjects displaying risk aversion or risk-loving tend to ignore private information when their prior beliefs on the asset fundamentals are strong. Consequently, private information struggles penetrating trading prices. The authors find evidence of non-Bayesian belief updating (confirmation bias and under-confidence). This reduces (improves) market efficiency when subjects’ prior beliefs are weak (strong).risk attitude; financial market; information; belief; risk-neutral information

Bayesian functional linear regression with sparse step functions

The functional linear regression model is a common tool to determine the relationship between a scalar outcome and a functional predictor seen as a function of time. This paper focuses on the Bayesian estimation of the support of the coefficient function. To this aim we propose a parsimonious and adaptive decomposition of the coefficient function as a step function, and a model including a prior distribution that we name Bayesian functional Linear regression with Sparse Step functions (Bliss). The aim of the method is to recover areas of time which influences the most the outcome. A Bayes estimator of the support is built with a specific loss function, as well as two Bayes estimators of the coefficient function, a first one which is smooth and a second one which is a step function. The performance of the proposed methodology is analysed on various synthetic datasets and is illustrated on a black P\'erigord truffle dataset to study the influence of rainfall on the production

Semiclassical and spectral analysis of oceanic waves

In this work we prove that the shallow water flow, subject to strong wind forcing and linearized around an adequate stationary profile, develops for large times closed trajectories due to the propagation of Rossby waves, while Poincar\'e waves are shown to disperse. The methods used in this paper involve semi-classical analysis and dynamical systems for the study of Rossby waves, while some refined spectral analysis is required for the study of Poincar\'e waves, due to the large time scale involved which is of diffractive type

Effects of Immigration on Labour Markets and Government Budgets - An Overview

The paper provides an overview on recent trends of immigration in OECD countries and on the possible effects of immigration on labour markets and government budgets. It also discusses migration policies from an economic point of view. By bringing together a bulk of international literature on labour market and fiscal effects of migration in a systematic way it provides a framework for assessing the economic effects of migration and improving the knowledge base for migration policies.migration, labour markets, fiscal effects of migration

A bridge to a low carbon future? Modelling the long-term global potential of natural gas

This project uses the global TIMES Integrated Assessment Model in UCL (‘TIAM-UCL’) to provide robust quantitative insights into the future of natural gas in the energy system and in particular whether or not gas has the potential to act as a ‘bridge’ to a low-carbon future on both a global and regional basis out to 2050. This report first explores the dynamics of a scenario that disregards any need to cut greenhouse gas (GHG) emissions. Such a scenario results in a large uptake in the production and consumption of all fossil fuels, with coal in particular dominating the electricity system. It is unconventional sources of gas production that account for much of the rise in natural gas production; with shale gas exceeding 1 Tcm after 2040. Gas consumption grows in all sectors apart from the electricity sector, and eventually becomes cost effective both as a marine fuel (as liquefied natural gas) and in medium goods vehicles (as compressed natural gas). It next examines how different gas market structures affect natural gas production, consumption, and trade patterns. For the two different scenarios constructed, one continued current regionalised gas markets, which are characterised by very different prices in different regions with these prices often based on oil indexation, while the other allowed a global gas price to form based on gas supply-demand fundamentals. It finds only a small change in overall global gas production levels between these but a major difference in levels of gas trade and so conclude that if gas exporters choose to defend oil indexation in the short-term, they may end up destroying their export markets in longer term. A move towards pricing gas internationally, based on supply-demand dynamics, is thus shown to be crucial if the if they are to maintain their current levels of exports. Nevertheless, it is also shown that, regardless of how gas is priced in the future, scenarios leading to a 2oC temperature rise generally have larger pipeline and LNG exports than scenarios that lead to a higher temperature increase. For pipeline trade, the adoption of any ambitious emissions reduction agreement results in little loss of markets and could (if carbon capture and storage is available) actually lead to a much greater level of exports. For LNG trade, because of the significant role that gas can play in replacing future coal demand in the emerging economies in Asia, markets that are largely supplied by LNG at present, we demonstrate that export countries should actively pursue an ambitious global agreement on GHG emissions mitigation if they want to expand their exports. These results thus have important implications for the negotiating positions of gas-exporting countries in the ongoing discussions on agreeing an ambitious global agreement on emissions reduction