Role of surface-inoculated Debaryomyces hansenii and Yarrowia lipolytica strains in dried fermented sausage manufacture. Part 2: Evaluation of their effects on sensory quality and biogenic amine content

The aim was to study the effects of Debaryomyces hansenii and Yarrowia lipolytica strains, used with lactic acid starter cultures (Lactobacillus plantarum), in the manufacture of dried fermented sausages in order to understand their effects on volatile profile, biogenic amine content and sensory properties. The experimental data showed that every yeast strain produced a specific profile of volatile metabolic products. The yeasts also gave sausages with distinctive sensory properties. The degree of mincing also influenced these properties, but none of these factors had significant influence upon the accumulation of biogenic amines.     

Post-buckling dynamic behavior of self-assembled 3D microstructures

The paper presents the snap-through phenomenon in the case of micro fabricated clamped-clamped buckled beam. This dynamic post-buckling behavior is likely to occur in 3D microstructures when they are subjected to large vibration amplitudes. The main difference between this work and previous studies is the MEMS specific beam dimension, especially the large initial deflection of the buckled beam that involves the inversion of the two first resonance frequencies. The mathematical development allows showing how the vibration amplitude of the supporting base affects the post-buckling dynamic behavior of the beam. For each frequency, the limit between the stable behavior and the snap-through behavior is evaluated. Moreover, the effect of environment is taken into account from the damping point of view. Samples are fabricated and the experiment is described. Measurements are compared to the theoretical approach and the results are in good agreement with the proposed model.     

Generalized ordering-search for learning directed probabilistic logical models

Recently, there has been an increasing interest in directed probabilistic logical models and a variety of formalisms for describing such models has been proposed. Although many authors provide high-level arguments to show that in principle models in their formalism can be learned from data, most of the proposed learning algorithms have not yet been studied in detail. We introduce an algorithm, generalized ordering-search, to learn both structure and conditional probability distributions (CPDs) of directed probabilistic logical models. The algorithm is based on the ordering-search algorithm for Bayesian networks. We use relational probability trees as a representation for the CPDs. We present experiments on a genetics domain, blocks world domains and the Cora dataset. Editors: Stephen Muggleton, Ramon Otero, Simon Colton.     

Visualization of myocardial perfusion derived from coronary anatomy

Visually assessing the effect of the coronary artery anatomy on the perfusion of the heart muscle in patients with coronary artery disease remains a challenging task. We explore the feasibility of visualizing this effect on perfusion using a numerical approach. We perform a computational simulation of the way blood is perfused throughout the myocardium purely based on information from a three-dimensional anatomical tomographic scan. The results are subsequently visualized using both three-dimensional visualizations and bull's eye plots, partially inspired by approaches currently common in medical practice. Our approach results in a comprehensive visualization of the coronary anatomy that compares well to visualizations commonly used for other scanning technologies. We demonstrate techniques giving detailed insight in blood supply, coronary territories and feeding coronary arteries of a selected region. We demonstrate the advantages of our approach through visualizations that show information which commonly cannot be directly observed in scanning data, such as a separate visualization of the supply from each coronary artery. We thus show that the results of a computational simulation can be effectively visualized and facilitate visually correlating these results to for example perfusion data.     

Threshold protocols in survivor set systems

Many replication protocols employ a threshold model when expressing failures they are able to tolerate. In this model, one assumes that no more than t out of n components can fail, which is a good representation when failures are independent and identically distributed (IID). In many real systems, however, failures are not IID, and a straightforward application of threshold protocols yields suboptimal results. Here, we examine the problem of transforming threshold protocols into survivor-set protocols tolerating dependent failures. Our main goal is to show the equivalence between the threshold model and the core/survivor set model. Toward this goal, we develop techniques to transform threshold protocols into survivor set ones. Our techniques do not require authentication, self-verification or encryption. Our results show in one case that we can transform a threshold protocol to a subset by spreading a number of processes across processors. This technique treats a given threshold algorithm as a black box, and consequently can transform any threshold algorithm. However, it has the disadvantage that the transformation is not possible for all sets of survivor sets. The second technique instead focuses on transforming voters: functions that evaluate to a value out of a set of tallied values in a replication protocol. Voters are an essential part of many fault-tolerant protocols, and we show a universal way of transforming them. With such a transformation we expect that a large number of protocols in the literature can be directly transformed with our technique. It is still an open problem, however, if the two models are equivalent, and our results constitute an important first step in this direction.     

Full field measurement at the micro-scale using micro-interferometry

This paper presents micro-interferometry as a measurement technique to extract temperature profiles and/or mass transfer gradients rapidly and locally in micro-devices. Interferometry quantifies the phase change between two or more coherent light beams induced by temperature and/or mass concentration. Previous work has shown that temporal noise is a limiting factor in microscale applications. This paper examines phase stepping and heterodyne phase retrieval techniques with both CCD and CMOS cameras. CMOS cameras are examined owing to the high speed at which images can be acquired which is particularly relevant to heterodyne methods. It is found that heterodyne retrieval is five times better than phase stepping being limited to 0.01 rad or λ/628. This is twice the theoretical limit of λ/1,000. The technique is demonstrated for mixing in a T-junction with a 500 μm square channel and compared favourably to a theoretical prediction from the literature. Further issues regarding application to temperature measurements are discussed.