Modifications in stability and structure of whey protein-coated o/w emulsions by interacting chitosan and gum arabic mixed dispersions

The influence of chitosan and gum arabic mixtures on the behaviour of o/w emulsions has been investigated at pH = 3.0. The emulsion behaviour, properties and microstructure were found to be greatly dependent on the precise gum arabic to chitosan ratio. Mixing of gum arabic with chitosan leads to the formation of coacervates of a size dependent on their ratio. Incorporation of low gum arabic to chitosan weight ratios into whey protein-coated emulsions causes depletion flocculation and gravity-induced phase separation. Increasing the polysaccharide weight ratio further, a droplet network with a rather high viscosity (at low shear stress) is generated, which prevents or even inhibits phase separation. At even higher gum arabic to chitosan ratios, the emulsion droplets were immobilised into clusters of an insoluble ternary matrix. Although the emulsion droplet charge had the same sign as that of the coacervates, clusters of oil droplets in a ternary matrix were generated. A mechanism to explain the behaviour of the whey protein-stabilised o/w emulsions is described on the basis of confocal and phase contrast microscopic observations, rheological data, zeta potential measurements, particle size analysis and visual assessment of the macroscopic phase separation events.     

Optimal controller tuning for nonlinear processes

The present work proposes a systematic methodology for the optimal selection of controller parameters in the sense of minimizing a performance index, which is a quadratic function of the tracking error and the control effort. The performance index is calculated explicitly as an algebraic function of the controller parameters by solving Zubov's partial differential equation (PDE). Standard optimization techniques are then employed for the calculation of the optimal values of the controller parameters. The solution of Zubov's PDE is also used to estimate the closed-loop stability region for the chosen values of the controller parameters. The proposed approach is finally illustrated in a chemical reactor control problem.     

Fuzzy systems design: direct and indirect approaches

A systematic classification of the data-driven approaches for design of fuzzy systems is given in the paper. The possible ways to solve this modelling and identification problem are classified on the basis of the optimisation techniques used for this purpose. One algorithm for each of the two basic categories of design methods is presented and its advantages and disadvantages are discussed. Both types of algorithms are self-learning and do not require interaction during the process of fuzzy model design. They perform adaptation of both the fuzzy model structure (rule-base) and the parameters. The indirect approach exploits the dual nature of Takagi-Sugeno (TS) models and is based on recently introduced recursive clustering combined with Kalman filtering-based procedure for recursive estimation of the parameter of the local sub-models. Both algorithms result in finding compact and transparent fuzzy models. The direct approach solves the optimisation problem directly, while the indirect one decomposes the original problem into on-line clustering and recursive estimation problems and finds a sub-optimal solution in real-time. The later one is computationally very efficient and has a range of potential applications in real-time process control, moving images recognition, autonomous systems design etc. It is extended in this paper for the case of multi-input–multi-output (MIMO systems). Both approaches have been tested with real data from an engineering process.     

Occurrence of copper resistant mutants in the toxic cyanobacteria Microcystis aeruginosa: characterisation and future implications in the use of copper sulphate as algaecide

Freshwater toxic cyanobacteria are an increasing problem to human and animal health. Control of cyanobacteria in water supply reservoirs involves the use of algaecides, such as copper sulphate, usually in a repetitive way. Repercussions of recurrent algaecide treatments on cyanobacteria population dynamics remain still unknown. We studied the adaptation of cyanobacteria to lethal doses of copper sulphate by using Microcystis aeruginosa as an experimental model. A fluctuation analysis demonstrated that copper-resistant cells arise by spontaneous mutations that occur randomly prior to exposition to copper sulphate. The rate of spontaneous mutation from copper sensitivity to resistance was 1.76×10⁻⁶ mutants per cell division. Resistant mutants exhibited a diminished fitness in the absence of copper sulphate, but only these variants were able to grow at Cu²⁺ concentrations higher than 5.8 μM. In addition, copper-resistant cells were significantly smaller than wild-type ones. Warnings on the long-term consequences of repetitive algaecide treatments in water supplies are suggested.     

Evolvable social agents for bacterial systems modeling

We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.     

Õ(Congestion + Dilation) Hot-Potato Routing on Leveled Networks

We study packet routing problems, in which we are given a set of N packets which will be sent on preselected paths with congestion C and dilation D. For store-and-forward routing, in which nodes have buffers for packets in transit, there are routing algorithms with a performance that matches the lower bound Ω(C+D). Motivated from optical networks, we study hot-potato routing in which the nodes are bufferless. Due to the lack of buffers, in hot-potato routing the packets may be delayed more than in store-and-forward routing. An interesting question is how much is the performance of routing algorithms affected by the absence of buffers. Here, we answer this question for the class of leveled networks, in which the nodes are partitioned into L+1 distinct levels. We present a randomized hot-potato routing algorithm for leveled networks, which routes the packets in O((C + L) ln⁹ (LN)) time with high probability. For routing problems with dilation Ω(L), and where N is a polynonial in L, this bound is within polylogarithmic factors of the lower bound Ω(C+L). Our algorithm demonstrates that for such routing problems the benefit from using buffers is no more than polylogarithmic; thus, hot-potato routing is an efficient way to route packets in leveled networks. In hot-potato routing, due to the lack of buffers, the packets may not be able to remain on their preselected paths during the course of routing (while in store-and-forward routing the packets remain on their preselected paths). However, in our algorithm the actual path that each packet follows contains its original preselected path; thus the lower bound Ω(C+L) is also a lower bound for the new paths. Our algorithm is distributed, that is, routing decisions are taken locally at each node while packets are routed in the network. To our knowledge, this is the first hot-potato algorithm designed and analyzed, in terms of congestion and dilation, for leveled networks.     

Virtual museums for all: employing game technology for edutainment

Museums have started to realise the potential of new technologies for the development of edutainment content and services for their visitors. Virtual reality technologies promise to offer a vivid, enjoyable experience to the museums guests, but the cost in time, effort and resources can prove to be overwhelming. In this paper, we propose the use of 3D game technologies for the purpose of developing affordable, easy to use and pleasing virtual environments. To this end, we present a case study based on an already developed version of a virtual museum and a newly implemented version that uses game technologies. The informal assessment indicates that game technologies can offer a prominent and viable solution to the need for affordable desktop virtual reality systems.     

Nonlinear observer design for state and disturbance estimation

A new systematic framework for nonlinear observer design that allows the concurrent estimation of the process state variables together with key unknown process or sensor disturbances is proposed. The nonlinear observer design problem is addressed within a similar methodological framework as the one introduced in [N. Kazantzis, C. Kravaris, Nonlinear observer design using Lyapunov's auxiliary theorem, Systems Control Lett. 34 (1998) 241; A.J. Krener, M. Xiao, Nonlinear observer design in the Siegel domain, SIAM J. Control Optim. 41 (2002) 932.] for state estimation purposes only. From a mathematical standpoint, the problem under consideration is addressed through a system of first-order singular PDEs for which a rather general set of solvability conditions is derived. A nonlinear observer is then designed with a state-dependent gain that is computed from the solution of the system of singular PDEs. Under the aforementioned conditions, both state and disturbance estimation errors converge to zero with assignable rates. The convergence properties of the proposed nonlinear observer are tested through simulation studies in an illustrative example involving a biological reactor.     

Gaussian Mixture Clustering and Language Adaptation for the Development of a New Language Speech Recognition System

The porting of a speech recognition system to a new language is usually a time-consuming and expensive process since it requires collecting, transcribing, and processing a large amount of language-specific training sentences. This work presents techniques for improved cross-language transfer of speech recognition systems to new target languages. Such techniques are particularly useful for target languages where minimal amounts of training data are available. We describe a novel method to produce a language-independent system by combining acoustic models from a number of source languages. This intermediate language-independent acoustic model is used to bootstrap a target-language system by applying language adaptation. For our experiments, we use acoustic models of seven source languages to develop a target Greek acoustic model. We show that our technique significantly outperforms a system trained from scratch when less than 8 h of read speech is available     

Efficient bufferless packet switching on trees and leveled networks

In bufferless networks the packets cannot be buffered while they are in transit; thus, once injected, the packets have to move constantly. Bufferless networks are interesting because they model optical networks. The objective of this work is to demonstrate that efficient bufferless packet switching is achievable in particular, interesting network topologies.