Inactivation of Listeria monocytogenes using Water Bath Heat Treatment in Vacuum Packed Ricotta Salata Cheese Wedges

Ricotta salata cheese is frequently contaminated on the surface with Listeria monocytogenes. Water bath heat treatment in vacuum packed whole ricotta salata cheese wheels demonstrated to be effective in inactivating L. monocytogenes. However, the risk of cross‐contamination in ricotta salata wedges is increased during cheese cutting. Therefore, the effectiveness of heat treatment in ricotta salata wedges has to be demonstrated conducting a new validation study. In this study, 9 different time temperature combinations, 75, 85, and 90 °C applied for 10, 20, and 30 min each, were tested on artificially contaminated ricotta salata cheese wedges. The extent of the lethal effect on L. monocytogenes was assessed 1 and 30 d after the application of the hot water bath treatment. Five of 9 combinations, 75 °C for 30 min, 85 °C for 20, and 30 min, and 90°C for 20 and 30 min, demonstrated to meet the process criteria of at least 5 log reduction. Sensory analyses were also conducted in order to account for the potential impact on sensory features of ricotta salata wedges, which showed no significant differences between treatments.     

P300-based BCI mouse with genetically-optimized analogue control.

In this paper we propose a brain-computer interface (BCI) mouse based on P300 waves in electroencephalogram (EEG) signals. The system is analogue in that at no point a binary decision is made as to whether or not a P300 was actually produced in response to the stimuli. Instead, the 2-D motion of the pointer on the screen, using a novel BCI paradigm, is controlled by directly combining the amplitudes of the output produced by a filter in the presence of different stimuli. This filter and the features to be combined within it are optimised by an evolutionary algorithm.     

Robuste Stahlbauten bei Brandbelastungen

In diesem Aufsatz werden die Aspekte des baulichen Brandschutzes vorgestellt, bei denen die Robustheit der Tragkonstruktion eine zentrale Rolle spielt. Erläutert wird das Konzept des kontrollierten Einsturzverhaltens bei eingeschossigen Gebäuden. Außerdem wird die Robustheit von mehrgeschossigen Gebäuden diskutiert und exemplarisch an drei Beispielen vorgestellt. Robustness of steel constructions under fire load. In this article some applications of fire safety engineering are presented, where the concept of structural robustness plays a major role. First the collapse mode analysis of single‐storey buildings is explained and its application to industrial halls. Then the robustness in multi‐storey buildings is briefly discussed where the examples of local collapse of beam, column and wind bracing are presented.     

A deadlock detection tool for concurrent Java programs

This paper presents some issues related to the design and implementation of a concurrency analysis tool able to detect deadlock situations in Java programs that make use of multithreading mechanisms. An abstract formal model is generated from the Java source using the Java2Spin translator. The model is expressed in the PROMELA language, and the SPIN tool is used to perform its formal analysis. The paper mainly focuses on the design of the Java2Spin translator. A set of experiments, carried out to evaluate the performances of the analysis tool, is also presented. Copyright © 1999 John Wiley & Sons, Ltd.     

Characterisation of white vinegars of different sources with artificial neural networks

Wine and cider vinegars currently attract growing interest from consumers, giving rise to a consequent increase in supply. A full appreciation of their quality is only possible, however, through recognition of their superior quality when compared with vinegars produced from raw materials of inferior quality. Therefore, it is necessary to pinpoint the parameters that define the quality of these products. Chemico-physical and sensory analysis has been used to draw up artificial neural networks (ANNs), on the basis of a vast sampling of vinegars from various countries, produced from a variety of raw materials, that was already subjected to multivariate statistical analysis. Among the chemical parameters, polyalcohols and other elements such as pH, tartaric acid and proline proved to be highly reliable, whereas other volatile substances and the results of sensory analysis were not very discriminating and could not be used to re-classify samples of unknown origin. The positive results obtained indicate that ANNs are a powerful mathematical tool, since they can be used to construct models that predict the botanical origin of the product and to re-classify samples of unknown origin, without any initial restrictive hypothesis. © 1998 Society of Chemical Industry.