Implementation of food safety management systems in the UK

This paper reports the first stage of work being undertaken to understand the factors that have impacted on the current state of food safety in the UK food manufacturing sector. The paper first explores developments in international food safety regulation in general and in particular, the UK. Using a survey and case study methodology, the paper examines the response of food manufacturing enterprises to food safety regulation, and uses statistical techniques to investigate the effects of enterprise size on the drivers for, benefits of, and challenges to compliance. Further, the factors that influence the successful implementation of an integrated food safety management system are also examined. The results show a great deal of both statutory and private regulation that has incentivised enterprises. In response, enterprises have implemented integrated food safety management systems to proactively deal with the risks associated with food safety, however, enterprises claim that statutory regulations are biased towards consumers, without adequate impact assessments on all stakeholders within the chain, and hence causing industry to incur significant costs that could otherwise be avoided. Even though compliance with food safety regulation is burdensome, the cost of non-compliance will also be significant to enterprises. The findings also show that there is no significant effect of size of enterprise on the drivers, benefits and challenges to compliance with food safety regulation.     

Low-dissipation and low-dispersion fourth-order Runge–Kutta algorithm

An optimized explicit low-storage fourth-order Runge–Kutta algorithm is proposed in the present work for time integration. Dispersion and dissipation of the scheme are minimized in the Fourier space over a large range of frequencies for linear operators while enforcing a wide stability range. The scheme remains of order four with nonlinear operators thanks to the low-storage algorithm. Linear and nonlinear propagation problems are finally solved to illustrate the accuracy of the present Runge–Kutta scheme.     

A Survey of Desynchronization in a Polychronous Model of Computation

The synchronous hypothesis arose in the late Eighties as a conceptual framework for the computer-aided design of embedded systems. Along with this framework, the issue of desynchronization was simultaneously raised as the major topic of mapping the ideal communication and computation model of synchrony on realistic and distributed computer architectures.The aim of the present article is to survey the development of this topics in the particular yet promising model of one of the prominent environments that were build along these principles: Signal and its polychronous (synchronous multi-clocked) model of computation, before to give some hints and ideas about ongoing research addressing this issue.     

Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999

We used land surface temperature (LST) algorithms and NDVI values to estimate changes in vegetation in the European continent between 1982 and 1999 from the Pathfinder AVHRR Land (PAL) dataset. These two parameters are monitored through HANTS (Harmonic ANalysis of Time Series) software, which allows the simultaneous observation of mean value, first harmonic amplitude and phase behaviors in the same image. These results for each complete year of data show the effect of volcanic aerosols and orbital drift on PAL data. Comparison of time series of HANTS cloud-free time series with the original time series for various land cover proves that this software is useful for LST analysis, although primarily designed for NDVI applications. Comparison of yearly averages of HANTS LST over the whole Europe with air temperature confirms the validity of the results. Maps of the evolution for both parameters between periods 1982/1986 and 1995/1999 have been elaborated: NDVI data show the well confirmed trend of increase over Europe (up to 0.1 in NDVI), Southern Europe seeing a decrease in NDVI (− 0.02). LST averages stay stable or slightly decrease (up to − 1.5 K) over the whole continent, except for southern areas for which the increase is up to 2.5 K. These results evidence that arid and semi-arid areas of Southern Europe have become more arid, the rest of Europe seeing an increase in its wood land proportion, while seasonal amplitude in Northern Europe has decreased.     

Mutational analysis of a satellite phage activator

A culture medium, named olive juice broth, which resembles the natural environment of Lactobacillus plantarum in the traditional Spanish-style green olive fermentation was obtained from green olives. In this medium, the bacteriocin-producing L. plantarum LPCO10 strain was able to produce bacteriocin throughout the incubation time (15 days). Bacteriocin purification from olive juice broth was achieved by a protocol including ammonium sulphate precipitation of cell-free, L. plantarum LPCO10 culture supernatants, and cation-exchange, hydrophobic-interaction and reversed-phase chromatographies. In a series of mixed cultures in olive juice broth, L. plantarum LPCO10 was able to dominate the bacteriocin-sensitive L. plantarum 128/2 strain, whereas the non-bacteriocin-producing, LPCO10 strain derivative, L. plantarum 55-1 strain did not show such capability. These results indicated that olive juice broth may be a valuable experimental substitute for olive fermentation brine in gaining more knowledge about the role of the bacteriocin-producing L. plantarum strains in the control of the Spanish-style green olive fermentation.     

Full-field birefringence imaging by thermal-light polarization-sensitive optical coherence tomography. I. Theory

A method for measuring birefringence by use of thermal-light polarization-sensitive optical coherence tomography is presented. The use of thermal light brings to polarization-sensitive optical coherence tomography a resolution in the micrometer range in three dimensions. The instrument is based on a Linnik interference microscope and makes use of achromatic quarter-wave plates. A mathematical representation of the instrument is presented here, and the detection scheme is described, together with a discussion of the validity domain of the equations used to evaluate the birefringence in the presence of white-light illumination.     

Stability of feature selection algorithms: a study on high-dimensional spaces

With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive work on the stability of learning algorithms, the stability of feature selection algorithms has been relatively neglected. This study is an attempt to fill that gap by quantifying the sensitivity of feature selection algorithms to variations in the training set. We assess the stability of feature selection algorithms based on the stability of the feature preferences that they express in the form of weights-scores, ranks, or a selected feature subset. We examine a number of measures to quantify the stability of feature preferences and propose an empirical way to estimate them. We perform a series of experiments with several feature selection algorithms on a set of proteomics datasets. The experiments allow us to explore the merits of each stability measure and create stability profiles of the feature selection algorithms. Finally, we show how stability profiles can support the choice of a feature selection algorithm. Alexandros Kalousis received the B.Sc. degree in computer science, in 1994, and the M.Sc. degree in advanced information systems, in 1997, both from the University of Athens, Greece. He received the Ph.D. degree in meta-learning for classification algorithm selection from the University of Geneva, Department of Computer Science, Geneva, in 2002. Since then he is a Senior Researcher in the same university. His research interests include relational learning with kernels and distances, stability of feature selection algorithms, and feature extraction from spectral data. Julien Prados is a Ph.D. student at the University of Geneva, Switzerland. In 1999 and 2001, he received the B.Sc. and M.Sc. degrees in computer science from the University Joseph Fourier (Grenoble, France). After a year of work in industry, he joined the Geneva Artificial Intelligence Laboratory, where he is working on bioinformatics and datamining tools for mass spectrometry data analysis. Melanie Hilario has a Ph.D. in computer science from the University of Paris VI and currently works at the University of Geneva’s Artificial Intelligence Laboratory. She has initiated and participated in several European research projects on neuro-symbolic integration, meta-learning, and biological text mining. She has served on the program committees of many conferences and workshops in machine learning, data mining, and artificial intelligence. She is currently an Associate Editor of theInternational Journal on Artificial Intelligence Toolsand a member of the Editorial Board of theIntelligent Data Analysis journal.     

Modeling adaptive behaviors in Context UNITY

Context-aware computing refers to a paradigm in which applications sense aspects of the environment and use this information to adjust their behavior in response to changing circumstances. In this paper, we present a formal model and notation (Context UNITY) for expressing quintessential aspects of context-aware computations; existential quantification, for instance, proves to be highly effective in capturing the notion of discovery in open systems. Furthermore, Context UNITY treats context in a manner that is relative to the specific needs of an individual application and promotes an approach to context maintenance that is transparent to the application. In this paper, we construct the model from first principles, introduce its proof logic, and demonstrate how the model can be used as an effective abstraction tool for context-aware applications and middleware.