Relaxation time and conductivity of comb-like gel polymer electrolytes

Using the copolymer of acrylonitrile (AN), methyl methacrylate (MMA), and poly(ethylene glycol) methyl ether methacrylate as a backbone and poly(ethylene glycol) methyl ether (PEGME) with 1100 molecular weight as side chains, comb-like gel polymers and their Li salt complexes were synthesized. The dynamic mechanical properties and conductivities were investigated. Results showed that the gel copolymer electrolytes possess two glass transitions: alpha-transition and beta-transition. Based on the time-temperature equivalence principle, a master curve was constructed by selecting T. as reference temperature. By reference to T-0 = 50 degrees C, the relation between log c, and c was found to be linear. The master curves are displaced progressively to higher frequencies as the content of plasticizer is increased. The relation between log tau(p) and the content of plasticizer is also linear.

Effect of storage time and cryoprotectant concentrations on the fertilization rate and hatching rate of cryopreserved sperm in red seabream (Pagrus major Temminck & Schlegel, 1843)

This study examined the effects of storage time and cryoprotectant concentrations on the post-thaw sperm of red seabream, Pagrus major. Sperm treated with 12%, 15%, 18% and 21% DMSO were cryopreserved for 10, 30, 60 and 360 days, and fertilization and hatching rates were analysed. For all groups, there were no differences in the fertilization rates and hatching rates between sperm cryopreserved for < 60 days and fresh sperm (98.8 +/- 0.8%, 96.4 +/- 1.3%). However, for sperm cryopreserved for 360 days, both fertilization rates (88.6 +/- 3.0% to 7.0 +/- 1.9%) and hatching rates (79.4 +/- 7.2% to 3.3 +/- 0.8%) decreased drastically. Furthermore, the cryoprotectant concentrations affected sperm quality significantly (P < 0.05). When cryopreserved for 360 days, sperm treated with 15% DMSO obtained the best results compared with other concentrations. We suggest that 15% DMSO may be an effective cryoprotectant for long-term sperm cryopreservation of red seabream.

THE VARIATION AND MOVEMENT OF A KIND OF EDDIES IN SHELF SLOPE WATER

Considering the characteristics of the time and space scales of the eddies we established a quasi-static and quasi-geostrophic model to describe their variation and movement in shelf slope water. The analytical solution revealed the main properties of the variation: slow expansion and fast stagnation processes and the law of the eddy motion affected under the background field. All theoretical results are proved by satellite image measurements.

Reaction time and replenishment time of SP and CGRP after incision in rat skin

Background. the skin neurogenic inflammation is mainly related to Substance P (SP) and Calcitonin Gene-related Peptide (CGRP). There is no data on their availability in the dynamics of skin nerve endings, concerning their release and replenishment after a nociceptive stimulus, so this was investigated. Materials and methods. 25 rats were randomly distributed in 5 groups. the animals of the control group (CG) determined the baseline levels of neuropeptides in the skin. the groups S0 and S30 did not receive any cutaneous stimulus at 30 and 60 minutes, respectively. in the group S1, an incision stimulus was made at 30 minutes. in the group S31, a nociceptive stimulus was performed by subdermal scratching at 30 minutes and, at 60 minutes, the incision stimulus was carried out in the same location (nociceptive hyperstimulation). the skin samples of the other animals were harvested from the back 1 minute after their death. SP, pro-CGRP and CGRP were quantified by Western Blotting. Results. the incision stimulus released SP, S1 compared to S0 (p < 0.05) detected in the first minute, and the replenishment time was more than 30 minutes. Also, it cleaved pro-CGRP, S1 compared to S31 (p < 0.05) in the first minute, and its replenishment time less than 30 minutes. Release of CGRP was not detected. Conclusion. the incision released SP already detected in the first minute; its replenishment time is more than 30 minutes. the incision decreased pro-CGRP, also detected in the first minute; and its replenishment time is less than 30 minutes.

Approximation-based feature selection and application for algae population estimation

Q. Shen and R. Jensen, 'Approximation-based feature selection and application for algae population estimation,' Applied Intelligence, vol. 28, no. 2, pp. 167-181, 2008. Sponsorship: EPSRC RONO: EP/E058388/1

Association of candidate genes with flowering time and water-soluble carbohydrate content in Lolium perenne (L.)

Sk?t, L., Humphreys, J., Humphreys, M. O., Thorogood, D., Gallagher, J. A., Sanderson, R., Armstead, I. P., Thomas, I. D. (2007). Association of candidate genes with flowering time and water-soluble carbohydrate content in Lolium perenne (L.). Genetics, 177 (1), 535-547. Sponsorship: BBSRC RAE2008

Hippocampal Modulation of Recognition, Conditioning, Timing, and Space: Why So Many Functions?

Advanced Research Projects Agency (ONR N00014-92-J-4015); National Science Foundation (IRI-90-24877); Office of Naval Research (N00014-91-J-1309)

Roots and wings: orthodoxy, tradition, and creativity in Irish folk Catholicism

The present work is an exploration of the beliefs and practices of three lay Catholic devotional communities in and around the city of Cork, Ireland. The research is guided by the theory that folk, or popular, religion is a dynamic process in which individuals and groups utilise the resources of orthodoxy, popular tradition, and personal creativity, to better interpret, articulate, and create religious experiences. Ethnographic fieldwork was the principal method of data collection. Four areas of folk religion are given special attention: the use of religious narrative to represent and reproduce religious experience, the use of material artefacts to create channels for sacred presence and activity, the use of ritual and pilgrimage to establish sacred time and space, and the use of prayer to accomplish all of these goals. These sections are followed by a more holistic analysis of the material, a critical examination of the work, and suggestions for further research.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Computational modelling of multi-physics and multi-scale processes in parallel

This paper provides an overview of the developing needs for simulation software technologies for the computational modelling of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and space scales. Computational modelling of such problems requires software tech1nologies that enable the mathematical description of the interacting physical phenomena together with the solution of the resulting suites of equations in a numerically consistent and compatible manner. This functionality requires the structuring of simulation modules for specific physical phenomena so that the coupling can be effectively represented. These multi-physics and multi-scale computations are very compute intensive and the simulation software must operate effectively in parallel if it is to be used in this context. An approach to these classes of multi-disciplinary simulation in parallel is described, with some key examples of application to2 challenging engineering problems.

Pseudo-spectral solutions for fluid flow and heat transfer in electro-metallurgical applications

The pseudo-spectral solution method offers a flexible and fast alternative to the more usual finite element and volume methods, particularly when the long-time transient behaviour of a system is of interest. The exact solution is obtained at grid collocation points leading to superior accuracy on modest grids. Furthermore, the grid can be freely adapted in time and space to particular flow conditions or geometric variations, especially useful where strongly coupled, time-dependent, multi-physics solutions are investigated. Examples include metallurgical applications involving the interaction of electromagnetic fields and conducting liquids with a free surface. The electromagnetic field determines the instantaneous liquid volume shape, which then affects the electromagnetic field. A general methodology of the pseudo-spectral approach is presented, with several instructive example applications: the aluminium electrolysis MHD problem, induction melting in a cold crucible and the dynamics of AC/DC magnetically levitated droplets. Finally, comparisons with available analytical solutions and to experimental measurements are discussed.

Role of bonding time and temperature on the physical properties of coupled anisotropic conductive–nonconductive adhesive film for flip chip on glass technology

Using thermosetting epoxy based conductive adhesive films for the flip chip interconnect possess a great deal of attractions to the electronics manufacturing industries due to the ever increasing demands for miniaturized electronic products. Adhesive manufacturers have taken many attempts over the last decade to produce a number of types of adhesives and the coupled anisotropic conductive-nonconductive adhesive film is one of them. The successful formation of the flip chip interconnection using this particular type of adhesive depends on, among factors, how the physical properties of the adhesive changes during the bonding process. Experimental measurements of the temperature in the adhesive have revealed that the temperature becomes very close to the required maximum bonding temperature within the first 1s of the bonding time. The higher the bonding temperature the faster the ramp up of temperature is. A dynamic mechanical analysis (DMA) has been carried out to investigate the nature of the changes of the physical properties of the coupled anisotropic conductive-nonconductive adhesive film for a range of bonding parameters. Adhesive samples that are pre-cured at 170, 190 and 210°C for 3, 5 and 10s have been analyzed using a DMA instrument. The results have revealed that the glass transition temperature of this type of adhesive increases with the increase in the bonding time for the bonding temperatures that have been used in this work. For the curing time of 3 and 5s, the maximum glass transition temperature increases with the increase in the bonding temperature, but for the curing time of 10s the maximum glass transition temperature has been observed in the sample which is cured at 190°C. Based on these results it has been concluded that the optimal bonding temperature and time for this kind of adhesive are 190°C and 10s, respectively.

Venetian time and the meander

Argues that the past is necessary to architectural modernity for its self-definition. Goes on to look at Le Corbusier and the past in relation to his revolutionary architectural manifesto, 'Vers une architecture' (1923), and his and Tafuri's views on Venice. Also considers Le Corbusier's 'law of meander' as a strategy for urbanism and his Venice Hospital project