Intra-sexual competition alters the relationship between testosterone and ornament expression in a wild territorial bird

Open Access funded by Natural Environment Research Council Under a Creative Commons licensePeer reviewedPublisher PD

Power of incentives with motivated agents in public organizations.

Public service motivation is often considered as an argument for low- powered incentive schemes in the public sector. In this paper, we characterize the optimal contract between a public regulator and an altruistic agent according to the degree of public service motivation, when the type of the public service consumer is privately observed. We show that the requested effort is non decreasing with and can be higher than the first best level. Moreover we show that the agent is put on a high powered contract when some customers are served but that this contract is associated with different types of consumers according to : In contrast, the agent is never put on a cost-plus contract. Finally, we show that the first best allocation can be achieved under budget balance for a degree of altruism higher than a threshold that we characterize.regulation; power of incentive schemes; altruism; public organization; countervailing incentives;

Functional approach for excess mass estimation in the density model

We consider a multivariate density model where we estimate the excess mass of the unknown probability density $f$ at a given level $\nu>0$ from $n$ i.i.d. observed random variables. This problem has several applications such as multimodality testing, density contour clustering, anomaly detection, classification and so on. For the first time in the literature we estimate the excess mass as an integrated functional of the unknown density $f$. We suggest an estimator and evaluate its rate of convergence, when $f$ belongs to general Besov smoothness classes, for several risk measures. A particular care is devoted to implementation and numerical study of the studied procedure. It appears that our procedure improves the plug-in estimator of the excess mass.Comment: Published in at http://dx.doi.org/10.1214/07-EJS079 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

Sloshing in the LNG shipping industry: risk modelling through multivariate heavy-tail analysis

In the liquefied natural gas (LNG) shipping industry, the phenomenon of sloshing can lead to the occurrence of very high pressures in the tanks of the vessel. The issue of modelling or estimating the probability of the simultaneous occurrence of such extremal pressures is now crucial from the risk assessment point of view. In this paper, heavy-tail modelling, widely used as a conservative approach to risk assessment and corresponding to a worst-case risk analysis, is applied to the study of sloshing. Multivariate heavy-tailed distributions are considered, with Sloshing pressures investigated by means of small-scale replica tanks instrumented with d >1 sensors. When attempting to fit such nonparametric statistical models, one naturally faces computational issues inherent in the phenomenon of dimensionality. The primary purpose of this article is to overcome this barrier by introducing a novel methodology. For d-dimensional heavy-tailed distributions, the structure of extremal dependence is entirely characterised by the angular measure, a positive measure on the intersection of a sphere with the positive orthant in Rd. As d increases, the mutual extremal dependence between variables becomes difficult to assess. Based on a spectral clustering approach, we show here how a low dimensional approximation to the angular measure may be found. The nonparametric method proposed for model sloshing has been successfully applied to pressure data. The parsimonious representation thus obtained proves to be very convenient for the simulation of multivariate heavy-tailed distributions, allowing for the implementation of Monte-Carlo simulation schemes in estimating the probability of failure. Besides confirming its performance on artificial data, the methodology has been implemented on a real data set specifically collected for risk assessment of sloshing in the LNG shipping industry

Statistical learning for wind power : a modeling and stability study towards forecasting

We focus on wind power modeling using machine learning techniques. We show on real data provided by the wind energy company Ma{\"i}a Eolis, that parametric models, even following closely the physical equation relating wind production to wind speed are outperformed by intelligent learning algorithms. In particular, the CART-Bagging algorithm gives very stable and promising results. Besides, as a step towards forecast, we quantify the impact of using deteriorated wind measures on the performances. We show also on this application that the default methodology to select a subset of predictors provided in the standard random forest package can be refined, especially when there exists among the predictors one variable which has a major impact

Parasitized mates increase infection risk for partners

Peer reviewedPublisher PD

“Living on the edge” : the role of field margins for common vole (Microtus arvalis) populations in recently colonised Mediterranean farmland

Acknowledgments RRP was supported by a PhD-studentship from the University of Valladolid (co-funded by Banco Santander, RR 30/04/2014). Financial support was provided by ECOCYCLES (BIODIVERSA 2008, Era-net European project, EUI2008-03658 and NERC NE/G002045/1 to XL) and ECOVOLE projects (CGL2012-35348; Ministerio de Economía y Competitividad of Spain). The article also contributes to project ECOTULA (CGL2015-66962-C2-1-R). We held all the necessary licenses and permits for conducting this work (JJLL, FM and RRP held animal experimentation permits of level B for Spain, and a capture permit was provided by the Consejería de Fomento y Medio Ambiente, Junta de Castilla y León (Expte: EP/CYL/665/2014)). We thank two anonymous reviewers for providing and constructive comments to improve the manuscript.Peer reviewedPublisher PD

Risk sharing and moral hazard under prospective payment to hospitals : how to reimburse services for outlier patients

We analyze the regulation of a single health care provider (e.g. a hospital). According to several payment rules used in different countries, we consider a mixed linear payment in which the hospital is paid a fixed price per DRG (diagnosis related group) for most patients (inlier patients) and is reimbursed by a cost sharing payment for patients with exceptionally costly stays (outlier patients). Given this form of payment, we determine the optimal threshold above which to consider a patient as an outlier patient, as well as the optimal payment per DRG and the optimal cost sharing parameter. For the case where the regulator can use a two part tariff, we also determine the fixed charge the regulator has to impose in order to extract hospital rents. [Authors]]]> Financial Management, Hospital ; Diagnosis-Related Groups ; Risk Sharing, Financial eng oai:serval.unil.ch:BIB_397B1AA9E66E 2022-05-07T01:15:41Z <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> https://serval.unil.ch/notice/serval:BIB_397B1AA9E66E Parachlamydia acanthamoebae enters and multiplies within pneumocytes and lung fibroblasts info:doi:10.1016/j.micinf.2005.12.011 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.micinf.2005.12.011 info:eu-repo/semantics/altIdentifier/pmid/16697235 Casson, N. Medico, N. Bille, J. Greub, G. info:eu-repo/semantics/article article 2006-04 Microbes and Infection, vol. 8, no. 5, pp. 1294-300 info:eu-repo/semantics/altIdentifier/pissn/1286-4579 <![CDATA[Parachlamydia acanthamoebae is a Chlamydia-like organism that naturally infects free-living amoebae. P. acanthamoebae is a putative emerging agent of community-acquired and inhalation pneumonia that may enter and multiply within human macrophages. However, since Parachlamydia induces their apoptosis, macrophages may not represent a perennial niche for this obligate intracellular bacterium. Therefore, we investigated whether pneumocytes and lung fibroblasts are permissive to Parachlamydia infection and might act as a replicative niche. Entry of Parachlamydia into pneumocytes (A549) and lung fibroblasts (HEL) was confirmed by confocal and electron microscopy. In A549 cells, the mean number of Parachlamydia per cell increased 7-fold from day 0 to day 7, independently of the technique used to label the bacteria. The proportion of infected A549 cells also increased over time, whereas cell viability remained unaffected by Parachlamydia infection. The sustained (3 weeks) viability of Parachlamydia when incubated in the presence of A549 cells contrasted with that observed in the absence of cells. HEL cells were also permissive to Parachlamydia infection, as we observed a 3- to 4-fold increase in the mean number of bacteria per cell. In HEL cells, Parachlamydia retained some viability for 2 weeks. These findings demonstrate that Parachlamydia is able to enter and multiply within pneumocytes and fibroblasts. The viability of both cell types was not compromised after Parachlamydia infection. We therefore conclude that these cells may remain infected for a prolonged time and may represent an intrapulmonary niche for the strictly intracellular Parachlamydia. This indirectly supports the role of Parachlamydia as an agent of pneumonia