Predictions of segregation of granular material with the aid of PHYSICA, a 3-D unstructured finite-volume modelling framework

In this paper a continuum model for the prediction of segregation in granular material is presented. The numerical framework, a 3-D, unstructured grid, finite-volume code is described, and the micro-physical parametrizations, which are used to describe the processes and interactions at the microscopic level that lead to segregation, are analysed. Numerical simulations and comparisons with experimental data are then presented and conclusions are drawn on the capability of the model to accurately simulate the behaviour of granular matter during flow.

A 3-D well-differentiated model of pediatric bronchial epithelium demonstrates unstimulated morphological differences between asthmatic and nonasthmatic cells

There is a need for reproducible and effective models of pediatric bronchial epithelium to study disease states such as asthma. We aimed to develop, characterize, and differentiate an effective, an efficient, and a reliable three-dimensional model of pediatric bronchial epithelium to test the hypothesis that children with asthma differ in their epithelial morphologic phenotype when compared with nonasthmatic children. Primary cell cultures from both asthmatic and nonasthmatic children were grown and differentiated at the air-liquid interface for 28 d. Tight junction formation, MUC5AC secretion, IL-8, IL-6, prostaglandin E2 production, and the percentage of goblet and ciliated cells in culture were assessed. Well-differentiated, multilayered, columnar epithelium containing both ciliated and goblet cells from asthmatic and nonasthmatic subjects were generated. All cultures demonstrated tight junction formation at the apical surface and exhibited mucus production and secretion. Asthmatic and nonasthmatic cultures secreted similar quantities of IL-8, IL-6, and prostaglandin E2. Cultures developed from asthmatic children contained considerably more goblet cells and fewer ciliated cells compared with those from nonasthmatic children. A well-differentiated model of pediatric epithelium has been developed that will be useful for more in vivo like study of the mechanisms at play during asthma.

On-line Emotion Recognition in a 3-D Activation-Valence-Time Continuum using Acoustic and Linguistic Cues

For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.