Suitability,efficiency and microbiological safety of novel physical technologies for the processing of ready‐to‐eat meals,meats and pumpable products

Consumer studies and market reports show an increase in consumption of ready‐to‐eat (RTE) foods. Although conventional processing technologies can in most cases produce safe products, they can also lead to the degradation of nutritional compounds and negatively affect quality characteristics. Consumers strongly prefer food that is minimally processed with the maximum amount of health‐promoting substances. Novel processing technologies as pre‐ or post‐treatment decontamination methods or as substitutes of conventional technologies have the potential to produce foods that are safe, rich in nutrient content and with superior organoleptic properties. Combining novel with conventional processes can eliminate potential drawbacks of novel technologies. This review examines available scientific information and critically evaluates the suitability and efficiency of various novel thermal and nonthermal technologies in terms of microbial safety, quality as well as nutrient content on the production of RTE meals, meats and pumpable products.     

Kernel-based machine learning for fast text mining in R

Recent advances in the field of kernel-based machine learning methods allow fast processing of text using string kernels utilizing suffix arrays. kernlab provides both kernel methods’ infrastructure and a large collection of already implemented algorithms and includes an implementation of suffix-array-based string kernels. Along with the use of the text mining infrastructure provided by tm these packages provide R with functionality in processing, visualizing and grouping large collections of text data using kernel methods. The emphasis is on the performance of various types of string kernels at these tasks.     

Stackelberg Strategies for Selfish Routing in General Multicommodity Networks

A natural generalization of the selfish routing setting arises when some of the users obey a central coordinating authority, while the rest act selfishly. Such behavior can be modeled by dividing the users into an α fraction that are routed according to the central coordinator’s routing strategy (Stackelberg strategy), and the remaining 1−α that determine their strategy selfishly, given the routing of the coordinated users. One seeks to quantify the resulting price of anarchy, i.e., the ratio of the cost of the worst traffic equilibrium to the system optimum, as a function of α. It is well-known that for α=0 and linear latency functions the price of anarchy is at most 4/3 (J. ACM 49, 236–259, 2002). If α tends to 1, the price of anarchy should also tend to 1 for any reasonable algorithm used by the coordinator. We analyze two such algorithms for Stackelberg routing, LLF and SCALE. For general topology networks, multicommodity users, and linear latency functions, we show a price of anarchy bound for SCALE which decreases from 4/3 to 1 as α increases from 0 to 1, and depends only on α. Up to this work, such a tradeoff was known only for the case of two nodes connected with parallel links (SIAM J. Comput. 33, 332–350, 2004), while for general networks it was not clear whether such a result could be achieved, even in the single-commodity case. We show a weaker bound for LLF and also some extensions to general latency functions. The existence of a central coordinator is a rather strong requirement for a network. We show that we can do away with such a coordinator, as long as we are allowed to impose taxes (tolls) on the edges in order to steer the selfish users towards an improved system cost. As long as there is at least a fraction α of users that pay their taxes, we show the existence of taxes that lead to the simulation of SCALE by the tax-payers. The extension of the results mentioned above quantifies the improvement on the system cost as the number of tax-evaders decreases. Research of G. Karakostas supported by an NSERC Discovery Grant and MITACS. Research of S. Kolliopoulos partially supported by the University of Athens under the project Kapodistrias.     

Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands

We examine how to induce selfish heterogeneous users in a multicommodity network to reach an equilibrium that minimizes the social cost. In the absence of centralized coordination, we use the classical method of imposing appropriate taxes (tolls) on the edges of the network. We significantly generalize previous work (Yang and Huang in Transp. Res. Part B 38:1–15, [2004]; Karakostas and Kolliopoulos in Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 268–276, [2004]; Fleischer et al. in Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 277–285, [2004]) by allowing user demands to be elastic. In this setting the demand of a user is not fixed a priori but it is a function of the routing cost experienced, a most natural assumption in traffic and data networks. Research supported by MITACS and a NSERC Discovery grant.     

A Simulation Framework for Heterogeneous Agents

We introduce a generic simulation framework suitable for agent-based simulations featuring the support of heterogeneous agents, hierarchical scheduling, and flexible specification of design parameters. One key aspect of this framework is the design specification: we use a format based on the Extendible Markup Language (XML) that is simple-structured yet still enables the design of flexible models. Another issue in agent-based simulations, especially when ready-made components are used, is the heterogeneity arising from both the agents' implementations and the underlying platforms. To tackle such obstacles, we introduce a wrapper technique for mapping the functionality of agents living in an interpreter-based environment to a standardized JAVA interface, thus facilitating the task for any control mechanism (like a simulation manager) because it has to handle only one set of commands for all agents involved. Again, this mapping is made by an XML-based definition format. We demonstrate the technique by applying it to a simple sample simulation of two mass marketing firms operating in an artificial consumer environment.     

Effect of minerals on casein micelle stability of cows' milk

The effects of minerals on casein micelle stability of individual cows' milk, throughout a complete lactation, were investigated. Calcium and calcium ions, magnesium, phosphorus, sodium, potassium and citrate contents were analysed, together with the following physical properties of milk; pH, ethanol stability, rennet clotting time and coagulum firmness. There was an inverse non-linear relationship between free calcium ion concentration and ethanol stability (ES; r=0.84). Rennet coagulation time showed a weaker relationship with free calcium ion concentration (r=0.44) but a stronger relationship with pH (r=0.66). In addition, samples containing higher amounts of free calcium ions produced a firmer gel. Citrate in natural samples acts as a stabilizing factor, as it slightly improves milk stability. Potassium, on the other hand, exhibited a negative correlation, but only with rennet clotting time (r=-0.52). Throughout lactation the average values were; free Ca2+ concentration 1.88 mM, pH 6.63, ES 83.2% and clotting time 13.6 min. The equilibrium relationship between pH and free Ca2+ concentration was investigated by adjusting milk pH from 5.9 to 7.1, using acid and alkali. There was a good inverse linear relationship between pH and log (free Ca2+) for individual milk samples, with a gradient of -0.62 and a standard deviation of 0.042.