End consumer goods movement generation in French medium urban areas

End-consumer movements, defined as the movements made by the consumer transporting the purchased goods, are identified with shopping trips. Whereas the logistics movements (freight distribution and urban part of the supply chain) are well studied in city logistics and urban planning, the end-consumer movements are usually related only to people movements. This paper presents a new modelling approach to characterise the shopping trips within a city logistics point of view, in order to connect these movements with those belonging to urban freight distribution in the supply chain. We present a trip generation model built from the data of recent household trip surveys, more precisely for the urban community of Lyon (France). We present the main results produced by the various simulations in a short-term planning horizon.Urban freight; trip generation modelling; simulation; urban policy; decision-making support

Blood eosinophil count to predict bronchial eosinophilic inflammation in COPD.

No abstract available

EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis

This paper presents procedures for implementing the EM algorithm to compute REML estimates of variance covariance components in Gaussian mixed models for longitudinal data analysis. The class of models considered includes random coefficient factors, stationary time processes and measurement errors. The EM algorithm allows separation of the computations pertaining to parameters involved in the random coefficient factors from those pertaining to the time processes and errors. The procedures are illustrated with Pothoff and Roy's data example on growth measurements taken on 11 girls and 16 boys at four ages. Several variants and extensions are discussed

A quasi-score approach to the analysis of ordered categorical data via a mixed heteroskedastic threshold model

This article presents an extension of the methodology developed by Gilmour et al. [19], for ordered categorical data, taking into account the heterogeneity of residual variances of latent variables. Heterogeneity of residual variances is described via a structural linear model on log-variances. This method involves two main steps: i) a ’marginalization’ with respect to the random effects leading to quasi-score estimators; ii) an approximation of the variance-covariance matrix of the observations which leads to an analogue of the Henderson mixed model equations for continuous Gaussian data. This methodology is illustrated by a numerical example of footshape in sheep.Cet article présente une extension de la méthodologie développée par Gilmour et al. [19] dans le cas de variables qualitatives ordonnées, prenant en compte l’hétérogénéité des variances résiduelles des variables latentes. L’hétérogénéité des variances résiduelles est décrite par un modèle linéaire structurel sur les logarithmes des variances. Cette méthode comprend deux étapes principales : i) une « marginalisation » par rapport aux effets aléatoires qui conduit, grâce aux équations de quasi-score, à l’estimation des paramètres ; ii) une approximation de la matrice de variance-covariance des observations qui aboutit à un système analogue aux équations du modèle mixte d’Henderson dans le cas de variables continues gaussiennnes. Cette méthodologie est illustrée par un exemple sur la forme des pieds chez le mouton

Genetic analysis of growth curves using the SAEM algorithm

The analysis of nonlinear function-valued characters is very important in genetic studies, especially for growth traits of agricultural and laboratory species. Inference in nonlinear mixed effects models is, however, quite complex and is usually based on likelihood approximations or Bayesian methods. The aim of this paper was to present an efficient stochastic EM procedure, namely the SAEM algorithm, which is much faster to converge than the classical Monte Carlo EM algorithm and Bayesian estimation procedures, does not require specification of prior distributions and is quite robust to the choice of starting values. The key idea is to recycle the simulated values from one iteration to the next in the EM algorithm, which considerably accelerates the convergence. A simulation study is presented which confirms the advantages of this estimation procedure in the case of a genetic analysis. The SAEM algorithm was applied to real data sets on growth measurements in beef cattle and in chickens. The proposed estimation procedure, as the classical Monte Carlo EM algorithm, provides significance tests on the parameters and likelihood based model comparison criteria to compare the nonlinear models with other longitudinal methods

Increased Levels of Circulating IL-16 and Apoptosis Markers Are Related to the Activity of Whipple's Disease

BACKGROUND: Whipple's disease (WD) is an infectious disease caused by Tropheryma whipplei, which replicates in macrophages and induces the release of interleukin (IL)-16, a substrate of caspase 3, and macrophage apoptosis. The disease is characterized by intestinal, cardiac or neurological manifestations; its diagnosis is based on invasive analysis requiring tissue biopsies or cerebrospinal fluid puncture. The disease progression is slow and often complicated by relapses despite empirical antibiotic treatment. METHODOLOGY/PRINCIPAL FINDINGS: We monitored circulating levels of IL-16 and nucleosomes in 36 French patients with WD; among them, some patients were enrolled in a longitudinal follow-up. As compared to control subjects, the circulating levels of both IL-16 and nucleosomes were increased in untreated patients with WD presenting as intestinal, cardiac or neurological manifestations. This finding was specific to WD since the circulating levels of IL-16 and nucleosomes were not increased in patients with unrelated inflammatory diseases such as inflammatory bowel disease or Q fever endocarditis. We also found that increased levels of IL-16 and nucleosomes were related to the activity of the disease. Indeed, successful antibiotic treatment decreased those levels down to those of control subjects. In contrast, patients who suffered from relapses exhibited circulating levels of IL-16 and nucleosomes as high as those of untreated patients. CONCLUSIONS/SIGNIFICANCE: Circulating levels of both IL-16 and nucleosomes were increased in WD. This finding provides simple and non-invasive tools for the diagnosis and the prognosis of WD

Reverse engineering gene regulatory networks using approximate Bayesian computation

Gene regulatory networks are collections of genes that interact with one other and with other substances in the cell. By measuring gene expression over time using high-throughput technologies, it may be possible to reverse engineer, or infer, the structure of the gene network involved in a particular cellular process. These gene expression data typically have a high dimensionality and a limited number of biological replicates and time points. Due to these issues and the complexity of biological systems, the problem of reverse engineering networks from gene expression data demands a specialized suite of statistical tools and methodologies. We propose a non-standard adaptation of a simulation-based approach known as Approximate Bayesian Computing based on Markov chain Monte Carlo sampling. This approach is particularly well suited for the inference of gene regulatory networks from longitudinal data. The performance of this approach is investigated via simulations and using longitudinal expression data from a genetic repair system in Escherichia coli.Comment: 16 pages, 11 figure

Exergy Based Methodology for Optimized Integration of Heat Pumps in Industrial Processes

Industrial processes may use heat pumps to recover low grade heat or to combine heating and cooling needs. In many cases, this technology leads to reduced energy consumption and greenhouse gases emissions. In this paper, a methodology, based on exergy analysis of heat sources and heat sinks, helping in optimizing industrial heat pumps design is presented. The optimization variables are: the refrigerant choice (pure fluid, azeotropic mixture, non azeotropic mixture), the thermodynamic state of the refrigerant (subcritical, supercritical) and the architecture of the heat pump (heat pump in reverse series). The heat pump is modelled in Modelica language: pinch method is used to model the heat exchangers and the compressor model is based on an isentropic efficiency assumption. The objective function is the maximization of the exergy efficiency. Genetic algorithm is used to perform the optimisation. The methodology is applied on a case study of an industrial process where a fluid is heated from 60°C to more than 120°C, and industrial effluents are available at 50°C

Évreux – 16-16bis rue Isambard

Identifiant de l'opération archéologique : 3385 Date de l'opération : 1993 (SU) Inventeur(s) : Destable Jean-Louis (AFAN) ; Gerber Frédéric Cette opération, liée à un projet immobilier, a porté sur une parcelle de 600 m2, située à l'extérieur de l'agglomération gallo-romaine et hors de l'enceinte du XIVe s., à proximité de la porte Saint-Pierre, vois site G sur le plan général d’Évreux (Fig. n°1 : Localisation des opérations archéologiques en centre ville, plan général (Evreux)). Une voie ro..