Parallelised production of fine and calibrated emulsions by coupling flow-focusing technique and partial wetting phenomenon

The capacity of microfluidic technology to fabricate monodisperse emulsion droplets is well established. Parallelisation of droplet production is a prerequisite for using such an approach for making high-quality materials for either fundamental or industrial applications where product quantity matters. Here, we investigate the emulsification efficiency of parallelised drop generators based on a flow-focusing geometry when incorporating the role of partial wetting in order to make emulsion droplets with a diameter below 10 μm. Confinement intrinsically encountered in microsystems intensifies the role played by interfaces between liquids and solids. We thus take advantage of partial wetting to enhance the maximum confinement accessible due to liquid flow focusing. We compare the performances brought by partial wetting to more established routes such as step emulsification. We show that the step configuration and the partial wetting regime are both well suited for being parallelised and thus open the way to the production of fine and calibrated emulsions for further applications. Finally, this new route of emulsification that exploits partial wetting between the fluids and the channel walls opens possibilities to the formation of substantially smaller droplets, as required in many fields of application.     

Feature selection on probabilistic symbolic objects

In data analysis tasks, we are often confronted to very high dimensional data. Based on the purpose of a data analysis study, feature selection will find and select the relevant subset of features from the original features. Many feature selection algorithms have been proposed in classical data analysis, but very few in symbolic data analysis （SDA） which is an extension of the classical data analysis, since it uses rich objects instead to simple matrices. A symbolic object, compared to the data used in classical data analysis can describe not only individuals, but also most of the time a cluster of individuals. In this paper we present an unsupervised feature selection algorithm on probabilistic symbolic objects （PSOs）, with the purpose of discrimination. A PSO is a symbolic object that describes a cluster of individuals by modal variables using relative frequency distribution associated with each value. This paper presents new dissimilarity measures between PSOs, which are used as feature selection criteria, and explains how to reduce the complexity of the algorithm by using the discrimination matrix.     

Encapsulation of phase change materials with alginate modified by nanostructured sodium carbonate and silicate

The encapsulation of phase change materials (PCMs) as thermal energy storage materials is a big issue. PCM is usually encapsulated to avoid spillage, flammability and its reaction with the surrounding environment to improve its application. In the last decade, various methods have been employed and all kinds of microencapsulated PCM are produced. In this paper, we present a facile route to produce an encapsulated PCM with an organic and inorganic shell. The encapsulated phase change material (PCM) was prepared using a coaxial micro-fluidic system combined with an ionic cross-linking process. The alginate was used as the basic shell and a range of capsules was obtained by modifying the original shell using two inorganic components such as sodium carbonate and sodium silicate. Various samples, each with a different surrounding layer, were prepared by combining alginate calcium (Alg–Ca) as an organic shell with an inorganic component such as alginate calcium carbonate (Alg–CaCO3) and alginate calcium silicate (Alg–CaSiO3). In these experimental works, we have investigated the compatibility and the stability of capsules modified with the inorganic component. The scanning electron microscopy (SEM) technique and optical microscopy were utilized to study the capsule morphology. The chemical composition of the shell was evaluated by Fourier transform infrared spectroscopy (ATR-FTIR), thermogravimetry analysis and SEM coupled with the EDX analysis, and the capsule stability was estimated under an accelerated thermal cycling.     

UniformL 1-distance large deviations in nonparametric density estimation

In this paper, we are concerned with uniform large deviations probabilities for theL ₁-error in kernel density estimation. Several results are stated taking into account uniformity over classes of density functions as well as over families of kernels and intervals of smoothing parameters. Some limits are well-identified and are universal in the sense that they do not depend neither on the distribution of the observations nor on the estimation kernel. Our results allow to compare performances of the test based on theL ₁-deviation of the kernel density estimator to that of the Kolmogorov-Smirnov test when testing goodness-of-fit of composite hypotheses.     

Beneficial effect on serum apo AI, apo B and Lp AI levels of Ramadan fasting

To investigate the developmental distribution of cochlear nucleus (CN) astrocytes, we used immunocytochemical localization of glial fibrillary acidic protein (GFAP) and S100beta in rats at 0, 5, 10, 15, 21, 30 postnatal days plus the adult. Differential developmental trends were observed for both proteins. The spatial distribution showed a progressive increase of the number of GFAP-immunoreactive (GFAP-IR) astrocytes during development. GFAP positive cells occurred first in the granule cell domain of the ventral CN and in the molecular cell layer of the dorsal CN, then followed an outside to inside pattern of progression. The GFAP-IR reached an adult distribution 1 month after birth. By contrast with GFAP, the apparition of S100beta-immunoreactivity (S100beta-IR) was abrupt (between 0 and 5 days) followed by a rapid stabilization of density and distribution of IR cells (between 15 and 21 days). The developmental distribution of S100beta-IR cells occurred from the posterodorsal region and progressed toward a rostroventral direction. With contrast to GFAP-IR astrocytes, S100beta-positive cells were mainly restricted to the central part of the CN, while only few IR astrocytes were observed in the granule cell domain of the ventral CN or in the molecular cell layer of the dorsal CN. This differential distribution suggests that both antigens were expressed by two different cell populations at least, it is obvious during the first postnatal week. The gradual expression of GFAP and S100beta is interpreted as reflecting the time course of astrocytic maturation. These data suggest that the maturation of CN astrocytes may be linked to the final maturation of CN neurons.