Microbiological aspects and shelf life of processed seafood products

BACKGROUND: Fresh fish and seafoods are very perishable products mainly owing to microbial activity of specific spoilage micro‐organisms. Application of hurdle technology leads to a variety of processed products with extended shelf life. In this study, sensory evaluation and microbiological analysis were carried out on 17 processed seafood products stored at 4 °C to determine their shelf life and the predominant spoilage micro‐organisms. RESULTS: Shelf life determined by sensory analysis varied from 66 to 180 days depending on the product. The cause of spoilage for most of the products was the development of off‐flavours/off‐odours, while two products were rejected owing to oil discolouration. Pseudomonads were in most cases below detection limit. H₂S‐producing bacteria, Brochothrix thermosphacta and Enterobacteriaceae were below detection limit throughout the experiment. The predominant spoilage micro‐organisms were lactic acid bacteria and yeasts. Hygiene indicators such as Staphylococcus spp. and total coliforms were also below detection limit in all samples. CONCLUSION: Primarily the initial pH and secondarily the NaCl content determined shelf life duration. Under the applied conditions, lactic acid bacteria and yeasts predominated. The contribution of chemical oxidation and/or autolysis to spoilage and shelf life might be important for most of the products. © 2012 Society of Chemical Industry     

Physicochemical,textural and sensory properties of white soft cheese made from buffalo and cow milk mixtures

The physicochemical, textural and sensory properties of white soft cheeses made from three different buffalo and cow milk mixtures (100:0, 70:30 and 30:70) during 3‐month storage were studied. The increase in buffalo milk concentration resulted in increasing total cheese yield, dry matter (DM) and fat retention and fat in DM content. However, it caused reductions in moisture content, salt intake, hardness, chewiness, elasticity, sensory hardness and sensory cohesiveness of the samples. The percentage of water‐soluble nitrogen to total nitrogen increased during storage resulting in decreased fracturability, hardness (textural and sensory), cohesiveness (textural and sensory), springiness, chewiness and elasticity. The panellists evaluated the white soft cheese made with buffalo milk as the most acceptable.     

Polygeneration microgrids: A viable solution in remote areas for supplying power,potable water and hydrogen as transportation fuel

This paper presents the concept and the design of a hybrid renewable energy polygeneration microgrid along with its technical and economical evaluation. The energy of the sun and the wind is harvested by photovoltaics and a wind turbine. Besides that, the components of the microgrid include a battery bank, a Proton Exchange Membrane (PEM) fuel cell, a PEM electrolyzer, a metal hydride tank, a reverse osmosis desalination unit using energy recovery and a control system. The microgrid covers the electricity, transport and water needs and thus its products are power, hydrogen as transportation fuel and potable water through desalination. Hydrogen and the desalinated water also act as medium to long term seasonal storage. A design tool based on TRNSYS 16, GenOpt 2.0 and TRNOPT was developed using Particle Swarm Optimization method. The economic evaluation of the concept was based on the discounting cash flow approach. The Monte Carlo Simulation method was used in order to take uncertainty into account. A technically feasible polygeneration microgrid adapted to a small island is financially profitable with a probability of 90% for the present and 100% at the medium term.     

An improved neural network for fuzzy reasoning implementation

Neural networks or connectionist models are massively parallel interconnections of simple neurons that work as a collective system, can emulate human performance and provide high computation rates. On the other hand, fuzzy systems are capable to model uncertain or ambiguous situations that are so often encountered in real life. One way for implementing fuzzy systems is through utilizations of the expert system architecture. Recently, many attempts have been made to “fuse” fuzzy systems and neural nets in order to achieve better performance in reasoning and decision making processes. The systems that result from such a fusion are called neuro-fuzzy inference systems and possess combined features. The purpose of the present paper is to propose such a neuro-fuzzy system by extending and improving the system of Keller et al. (1992). The present system makes use of Hamacher's fuzzy intersection function and Sugeno's complement function. After a brief outline of the operation of the system its features are established with the aid of four theorems which are fully proved. The capabilities of the system are shown by a set of simulation results derived for the case of trapezoidal fuzzy sets. These results are shown to be better than the ones obtained with the original neuro-fuzzy system of Keller et al.     

Efficient VLSI array processing structures for adaptive quadratic digital filters

In this paper we introduce a class of efficient architectures for adaptive quadratic digital filters. These architectures are based on the LMS algorithm and use the rank compressed lower-upper (LU) triangular deomposition method. These architectures exhibit high parallelism as well as great modularity and regularity. We also consider affiliated VLSI array processing structures and compare these in terms of hardware cost and data throughput delay. For comparison purposes, the distributed arithmetic structures of adaptive quadratic filters are also included in the paper. Finally, the convergence performance of the adaptive quadratic filters is tested via benchmark simulation examples.This work was supported by National Science Foundation Grant ECS-8601307.     

Learning automata routeing in connection-oriented networks

Learning automata are used at the source nodes of a connection-oriented network to dynamically route newly arriving virtual calls to their destination. First, two new learning automata are introduced. Then, these two learning automata, as well as the well-known L Learning automaton and the deterministic shortest-path algorithms are used in a simulation program to route virtual calls. The more frequent the updating and the more recent network state information used, the better the performance. In the sequence, the virtual link length is developed as a function of both the number of packets and the number of virtual calls at the network link. This virtual link length is used in the learning automata routeing algorithm and is shown via simulation to be superior to the minimum packet delay or shortest-queue-type link length, usually used in real networks. Thus, in connection-oriented networks, not only the packet but also the virtual call traffic characteristics should be used in the routeing decisions. Furthermore, when the network state information is out-of-date, or when there are few virtual calls and each one carries a large number of packets, then the virtual link length should be based more on the number of virtual calls than on the number of packets at this link. On the other hand, when the network state information is current and there are many virtual calls and each one carries a small number of packets, then the virtual link length should be based more on the number of packets than on the number of virtual calls at this link.     

The impact of on-demand metacognitive help on effortful behaviour: A longitudinal study using task-related visual analytics

This longitudinal study investigates the differences in learners' effortful behaviour over time due to receiving metacognitive help—in the form of on-demand task-related visual analytics. Specifically, learners' interactions (N = 67) with the tasks were tracked during four self-assessment activities, conducted at four discrete points in time, over a period of 8 weeks. The considered and coded time points were: (a) prior to providing the metacognitive help; (b) while the task-related visual analytics were available (treatment); (c) after the removal of the treatment; and (d) while the option to receive metacognitive help was available again. To measure learners' effortful behaviour across the self-assessment activities, this study utilized learners' response-times to correctly/wrongly complete the tasks and on-task effort expenditure. The panel data analysis shown that the usage of metacognitive help caused statistically significant changes in learners' effortful behaviour, mostly in the third and fourth phase. Statistically significant changes were detected also in the usage of metacognitive help. These results provide empirical evidence on the benefits of task-related visual analytics to support learners' on-task engagement, and suggest relevant cues on how metacognitive help could be designed and prompted by focusing on the “task”, instead of the “self”.     

Fluorescence anisotropy based single liposome assay to measure molecule-membrane interactions

Nanometer-scaled liposomes are used frequently for research, therapeutic, and analytical applications as carriers for water-soluble molecules. Recent technical advances allow the monitoring of single liposomes, which provides information on heterogeneous properties that were otherwise hidden due to ensemble averaging. Recent observations demonstrated that the efficiency of entrapping water-soluble molecules increases with decreasing vesicle size. The molecular mechanism behind this observation is not clear, but enhanced molecule-membrane interactions due to the increase of the surface area-to-volume ratio could play an important role. To investigate this hypothesis, we extended our single liposome assay based on confocal fluorescence imaging by implementation of fluorescence anisotropy. This combination has not been widely exploited, and confocal fluorescence anisotropy imaging in particular has seldom been used. We investigated different small dye molecules and were able to determine if these molecules interact or not with the liposome membrane. We confirm the liposome size-dependent entrapment of molecules whereas the molecule-membrane interactions appear to be independent of liposome size. Our fluorescence anisotropy assay can be used as a general method to investigate molecule-membrane interactions or molecule-molecule interactions in a high-throughput manner in nanometer-scaled containers like liposomes.     

Statistical Properties for the Envelope and Phase of the α ? η ? μ Generalized Fading Channels

In this paper, a study on the statistical properties for the envelope and phase of both formats of the ?? ? ?? ? ?? generalized fading channels is provided by deriving novel closed-form expressions. Specifically, a simple and closed-form expression for the phase crossing rate of the ?? ? ?? ? ?? generalized fading channels is obtained. Moreover, exact analytical expressions for the level crossing rate and the average duration of fades, as well as the PDF of random FM noise are presented. Confirmation of the provided analytical formulations is attained by reducing the general model to some widely known special cases (Nakagami-m, Hoyt, and Rayleigh). Extra validation is performed by means of a sample of numerical results obtained by Monte Carlo simulation.