Digital microfluidic design and optimization of classic and new fluidic functions for lab on a chip systems

This paper deals with microfluidic studies for lab-on-a-chip development. The first goal was to develop microsystems immediately usable by biologists for complex protocol integrations. All fluid operations are performed on nano-liter droplet independently handled solely by electrowetting on dielectric (EWOD) actuation. A bottom-up architecture was used for chip design due to the development and validation of elementary fluidic designs, which are then assembled. This approach speeds up development and industrialization while minimizing the effort in designing and simplifying chip-fluidic programming. Dispensing reproducibility for 64 nl droplets obtained a CV below 3% and mixing time was only a few seconds. Ease of the integration was demonstrated by performing on chip serial dilutions of 2.8-folds, four times. The second part of this paper concerns the development of new innovative fluidic functions in order to extend EWOD-actuated digital fluidics’ capabilities. Experiments of particle dispensing by EWOD droplet handling are reported. Finally, work is shown concerning the coupling of EWOD actuation and magnetic fields for magnetic bead manipulation.     

A new supervised classification algorithm in artificial immune systems with its application to carotid artery Doppler signals to diagnose atherosclerosis

Because of its self-regulating nature, immune system has been an inspiration source for usually unsupervised learning methods in classification applications of Artificial Immune Systems (AIS). But classification with supervision can bring some advantages to AIS like other classification systems. Indeed, there have been some studies, which have obtained reasonable results and include supervision in this branch of AIS. In this study, we have proposed a new supervised AIS named as Supervised Affinity Maturation Algorithm (SAMA) and have presented its performance results through applying it to diagnose atherosclerosis using carotid artery Doppler signals as a real-world medical classification problem. We have employed the maximum envelope of the carotid artery Doppler sonograms derived from Autoregressive (AR) method as an input of proposed classification system and reached a maximum average classification accuracy of 98.93% with 10-fold cross-validation method used in training-test portioning. To evaluate this result, comparison was done with Artificial Neural Networks and Decision Trees. Our system was found to be comparable with those systems, which are used effectively in literature with respect to classification accuracy and classification time. Effects of system's parameters were also analyzed in performance evaluation applications. With this study and other possible contributions to AIS, classification algorithms with effective performances can be developed and potential of AIS in classification can be further revealed.     

PCI总线在双谱段探测系统中的应用*

PCI是DSP应用系统与通用计算机高速通信的理想接口。介绍了一种双谱段探测系统的PCI接口方案,该方案采用TI公司的TMS320F2812 DSP作为控制单元主控芯片,采用Cypress公司PCIDP系列的CY7C09449PV作为PCI接口芯片,具有接口简单方便易于实现的优点。详细讨论了CY7C09449PV与TMS320F2812的硬件连接、参数配置与时序分析。     

Dynamical sources in information theory: Fundamental intervals and word prefixes

A quite general model of source that comes from dynamical systems theory is introduced. Within this model, some basic problems of algorithmic information theory contexts are analysed. The main tool is a new object, the generalized Ruelle operator, which can be viewed as a “generating” operator for fundamental intervals (associated to information sharing common prefixes). Its dominant spectral objects are linked with important parameters of the source, such as the entropy, and play a central rôle in all the results.     

Internationale Zusammenarbeit zum Nachweis bestrahlter Lebensmittel

Zusammenfassung Es wird eine Übersicht über die neuesten internationalen Entwicklungen, insbesondere die Programme von ADMIT (FAO/IAEA) und dem BCR (Europäische Gemeinschaft) zum Nachweis einer erfolgten Bestrahlung von Lebensmitteln gegeben. Eine Kontrolle bestrahlter Lebensmittel direkt am Produkt ist wünschenswert, um Kennzeichnung und eventuell bestehende Verbote zu überwachen, aber auch um das Vertrauen des Verbrauchers in eine korrekte Anwendung des Verfahrens zu stärken und sein Recht auf freie Wahl zwischen bestrahlten und unbestrahlten Lebensmitteln zu schützen. Auf internationaler Ebene haben bereits mehrere größere Ringversuche stattgefunden, z. B. Messung der Elektronen-Spin-Resonanz in Knochen von Geflügel, Schwein, Rind, Froschschenkeln und Fisch; Messung der Thermoluminescenz von unlöslichen Mineralien, isoliert aus Gewürzen und Kräutern; die gaschroma- tographische Analyse von Kohlenwasserstoffen und Alkylcyclobutanonen aus der Lipidfraktion von Hähnchen; und die mikrobiologische DEFT/APC-Analyse von Gewürzen. Diese Methoden sollen in naher Zukunft als internationale Standardmethoden etabliert werden.

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International co-operation in the field of detection of irradiated food

A survey over recent international developments to detect the irradiation treatment of foods is given, in particular the programmes of ADMIT (FAO/ IAEA) and of BCR (European Community). The need to detect radiation treatment by analysing the food itself is desirable to check compliance with existing regulations, such as the enforcement of labelling and control of prohibition, to enhance consumer confidence in the correct application of radiation processing, and to protect consumers' freedom of choice between irradiated or unirra-diated food products. Some larger collaborative studies on an international scale have already taken place, e.g. ESR measurements of bones from chicken, pork, beef, frog legs and fish, thermoluminescence of insoluble minerals isolated from herbs and spices, gas Chromatographic analysis of hydrocarbons and alkylcyclobutanones derived from the lipid fraction of chicken and the microbiological DEFT/APC procedure for spices. These methods could soon be implemented in international standard protocols.

     

Optimising Reliability: Portfolio Modeling of Contract Types for Retail Water Providers

This paper considers the retail water provider’s purchasing decision of a portfolio of permanent contracts from wholesalers with multiple volatile water sources. We consider the reliability of two contract types: (1) fixed annual quantities, and (2) an inflow harvest function with storage. Our four-reservoir case in Sydney (Australia) has cross-correlated inflow data. To accommodate multi-reservoir cross-correlation we adapt Portfolio Theory from finance to lognormal reservoir inflows, re-framing traditional storage theory from the wholesaler’s optimal operating policy to the retailer’s optimal purchasing policy. We find that Reliability improves with access to a source pool (cf. fixed quantities from separate sources), demonstrating the ‘insurance effect’, and the portfolio that minimises lognormal variance also minimises harvest (and thus environmental impact). Reform direction in Australian (and other international) water markets is towards multi-provider vertical disintegration, which may reduce pool opportunities and negate the insurance effect. We consider diminishing reliability returns as reservoir harvesting increases, and conclude a retail portfolio of permanent contracts from reservoirs, plus short-term contracts from alternative sources (either independently or negatively cross-correlated) efficiently secures high reliability. The challenge in incomplete water markets remains in encouraging and sustaining supply diversification that may only be needed aperiodically during extreme droughts.     

NAROAS: a neural network-based advanced operator support system for the assessment of systems reliability

We have developed and implemented a computerized reliability monitoring system for nuclear power plant applications, based on a neural network. The developed computer program is a new tool related to operator decision support systems, in case of component failures, for the determination of test and maintenance policies during normal operation or to follow an incident sequence in a nuclear power plant. The NAROAS (Neural Network Advanced Reliability Advisory System) computer system has been developed as a modularized integrated system in a C++ Builder environment, using a Hopfield neural network instead of fault trees, to follow and control the different system configurations, for interventions as quickly as possible at the plant. The observed results are comparable and similar to those of other computer system results. As shown, the application of this neural network contributes to the state of the art of risk monitoring systems by turning it easier to perform online reliability calculations in the context of probabilistic safety assessments of nuclear power plants.