Anne-Françoise Yao

A kernel spatial density estimation allowing for the analysis of spatial clustering. Application to Monsoon Asia Drought Atlas data

A nonparametric density estimate that incorporates spatial dependency has not been studied in the literature. In this article, we propose a new spatial density estimator that depends on two kernels: one controls the distance between observations while the other controls the spatial dependence structure. The uniform almost sure convergence of the density estimate is established with the rate of convergence. The consistency of the mode of this kernel density is also studied. Then a spatial hierarchical unsupervised clustering algorithm based on the mode estimate is presented. Some simulations as well as an application to the Monsoon Asia Drought Atlas data illustrate the efficiency of our algorithm, and a comparison of the spatial structures of these data detected by the density estimate and clustering algorithm are done.

Development and validation of a new dynamic computer-controlled model of the human stomach and small intestine.

For ethical, regulatory, and economic reasons, in vitro human digestion models are increasingly used as an alternative to in vivo assays. This study aims to present the new Engineered Stomach and small INtestine (ESIN) model and its validation for pharmaceutical applications. This dynamic computer‐controlled system reproduces, according to in vivo data, the complex physiology of the human stomach and small intestine, including pH, transit times, chyme mixing, digestive secretions, and passive absorption of digestion products. Its innovative design allows a progressive meal intake and the differential gastric emptying of solids and liquids. The pharmaceutical behavior of two model drugs (paracetamol immediate release form and theophylline sustained release tablet) was studied in ESIN during liquid digestion. The results were compared to those found with a classical compendial method (paddle apparatus) and in human volunteers. Paracetamol and theophylline tablets showed similar absorption profiles in ESIN and in healthy subjects. For theophylline, a level A in vitro–in vivo correlation could be established between the results obtained in ESIN and in humans. Interestingly, using a pharmaceutical basket, the swelling and erosion of the theophylline sustained release form was followed during transit throughout ESIN. ESIN emerges as a relevant tool for pharmaceutical studies but once further validated may find many other applications in nutritional, toxicological, and microbiological fields. Biotechnol. Bioeng. 2016;113: 1325–1335.

Nonparametric prediction of spatial multivariate data

This paper investigates a nonparametric spatial predictor of a stationary multidimensional spatial process observed over a rectangular domain. The proposed predictor depends on two kernels in order to control both the distance between observations and that between spatial locations. The uniform almost complete consistency and the asymptotic normality of the kernel predictor are obtained when the sample considered is an alpha-mixing sequence. Numerical studies were carried out in order to illustrate the behaviour of our methodology both for simulated data and for an environmental data set.

Nonparametric prediction in the multivariate spatial context

This paper investigates a nonparametric spatial predictor of a stationary multidimensional spatial process observed over a rectangular domain. The proposed predictor depends on two kernels in order to control both the distance between observations and that between spatial locations. The uniform almost complete consistency and the asymptotic normality of the kernel predictor are obtained when the sample considered is an alpha-mixing sequence. Numerical studies were carried out in order to illustrate the behaviour of our methodology both for simulated data and for an environmental data set.