Equiangular spiral micro-structured waveguides in lithium niobate

Buried, micro-structured waveguides with an equiangular spiral geometry, which can be formed in a lithium niobate crystal by direct femtosecond laser writing, are analysed with the full-vectorial finite element method. The guiding properties of such waveguides are presented.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Structured codebooks for SCS watermarking

Digital watermarking aims at embedding information in digital data. The watermark is usually required to be imperceptible, unremovable and to have a high information content. Unfortunately, these three requirements are contradicting. For example, having a more robust watermark makes it either more perceptible or/and less informative. For Gaussian data and additive white Gaussian noise, an optimal but also impractical scheme has already be devised. Since then, many practical schemes have tried to approach the theoretical limits. This paper investigate improvements to current state-of-the-art embedding schemes.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Structured engagement in the extended enterprise

Discusses the necessity for the conscious recognition of the phenomenon known as the extended enterprise; this demands that product, process and supply chain design are all considered simultaneously. Structure must be given to the extended enterprise in order to understand and manage it efficaciously. The authors discuss multiple perspectives for doing this, and employ the notions of “3-dimensional concurrent engineering” and “holonic thinking” for conceiving what the structure may look like. Describes a current “action research” project that is investigating potential lead-time reductions within an extended enterprise’s product introduction process. This aims to produce process visualisations, a framework for structuring and sychronising phases and stage-gates within the extended enterprise, and a new simulation tool which will provide a synthetic distributed hypermedia network. These deliverables will be used to play strategic “games” to explore problem issues within the product introduction process that belongs to the extended enterprise, develop teamwork across autonomous companies, and ultimately, contribute to the design of future extended enterprise supply chains.

Practices and views on fetal heart monitoring:A structured observation and interview study

Objective: To assess and explain deviations from recommended practice in National Institute for Clinical Excellence (NICE) guidelines in relation to fetal heart monitoring. Design: Qualitative study. Setting: Large teaching hospital in the UK. Sample: Sixty-six hours of observation of 25 labours and interviews with 20 midwives of varying grades. Methods: Structured observations of labour and semistructured interviews with midwives. Interviews were undertaken using a prompt guide, audiotaped, and transcribed verbatim. Analysis was based on the constant comparative method, assisted by QSR N5 software. Main outcome measures: Deviations from recommended practice in relation to fetal monitoring and insights into why these occur. Results: All babies involved in the study were safely delivered, but 243 deviations from recommended practice in relation to NICE guidelines on fetal monitoring were identified, with the majority (80%) of these occurring in relation to documentation. Other deviations from recommended practice included indications for use of electronic fetal heart monitoring and conduct of fetal heart monitoring. There is evidence of difficulties with availability and maintenance of equipment, and some deficits in staff knowledge and skill. Differing orientations towards fetal monitoring were reported by midwives, which were likely to have impacts on practice. The initiation, management, and interpretation of fetal heart monitoring is complex and distributed across time, space, and professional boundaries, and practices in relation to fetal heart monitoring need to be understood within an organisational and social context. Conclusion: Some deviations from best practice guidelines may be rectified through straightforward interventions including improved systems for managing equipment and training. Other deviations from recommended practice need to be understood as the outcomes of complex processes that are likely to defy easy resolution. © RCOG 2006.

Synthesis and evaluation of scintillant-containing poly(oxyethylene glycol) polymer (POP-Sc) supports

Co-polymerisation of α-styryl-poly(ethylene glycol)300, α,ω-bis(styryl)-penta(ethylene glycol) and 2,5-diphenyl-4-(4′-vinylbenzyl)oxazole in varying molar ratios resulted in the production of chemically functionalised scintillant-containing poly(oxyethylene glycol) polymer (POP-Sc) supports. These materials are compatible with both aqueous and organic solvents, and possess the ability to scintillate efficiently in the presence of ionising radiation, even after prolonged and repeated exposure to organic solvents. The utility of POP-Sc supports in both solid-phase peptide chemistry and a functional scintillation proximity assay has been exemplified.

Control of the properties of micro-structured waveguides in lithium niobate crystal

We study numerically depressed-index cladding, buried, micro-structured optical waveguides that can be formed in a lithium niobate crystal by femtosecond laser writing. We demonstrate to which extent the waveguiding properties can be controlled by the waveguide geometry at the relatively moderate induced refractive index contrasts that are typical of the direct femtosecond inscription.

Structured packing in air distillation

An economic analysis has been performed to establish when it is advantageous to use structured packing in air separation plant. A model of a low pressure cycle was developed to calculate the power saved when packing is used, and cost models were developed for the columns and cold box. The rate of return was calculated on the extra investment required for a packed plant based on the annual power saving. Structured packing was found to be economic only in larger plants, where economies of scale mean that the increased capital cost becomes less significant compared with the power saved. It was also found that different sized plants favour different packings. The analysis identified that the packing variable with the biggest impact on the economic balance was the efficiency and that increasing the efficiency of current packings could enhance their balance in air distillation. A new packing was therefore developed to have a higher efficiency than conventional ones. The vapour phase resistance was targeted for reduction, since most packing models predict this to be dominant. The final shape was chosen as the easiest and most economic to make. It has converging and diverging channels and was manufactured in two specific areas and with two block heights by Tianjin University Packing Factory. A 0.3 m diameter distillation column test rig was designed, built and commissioned with the standard Sulzer Mellapak 500YW. It was then used to test the new packing alongside some standard ones. Because the packings had different specific areas, correlations of published results were developed to allow a true comparison to be made. The test results show that, unexpectedly, the packings with 0.1 m high blocks have an efficiency about 8% greater than the standard 0.2 m blocks. The new shape as implemented in the 350Y packing shows an additional 7% greater efficiency, so it is 15% better than a standard packing with the same area. It has a better efficiency than the Mellapak 500YW and the higher capacity associated with its lower area. The new 500Y did not show a significant advantage.

Computational fluid dynamical studies of structured distillation packings

In recent years structured packings have become more widely used in the process industries because of their improved volumetric efficiency. Most structured packings consist of corrugated sheets placed in the vertical plane The corrugations provide a regular network of channels for vapour liquid contact. Until recently it has been necessary to develop new packings by trial and error, testing new shapes in the laboratory. The orderly repetitive nature of the channel network produced by a structured packing suggests it may be possible to develop improved structured packings by the application of computational fluid dynamics (CFD) to calculate the packing performance and evaluate changes in shape so as to reduce the need for laboratory testing. In this work the CFD package PHOENICS has been used to predict the flow patterns produced in the vapour phase as it passes through the channel network. A particular novelty of the approach is to set up a method of solving the Navier Stokes equations for any particular intersection of channels. The flow pattern of the streams leaving the intersection is then made the input to the downstream intersection. In this way the flow pattern within a section of packing can be calculated. The resulting heat or mass transfer performance can be calculated by other standard CFD procedures. The CFD predictions revealed a circulation developing within the channels which produce a loss in mass transfer efficiency The calculations explained and predicted a change in mass transfer efficiency with depth of the sheets. This effect was also shown experimentally. New shapes of packing were proposed to remove the circulation and these were evaluated using CFD. A new shape was chosen and manufactured. This was tested experimentally and found to have a higher mass transfer efficiency than the standard packing.

Data visualisation and exploration with prior knowledge

Visualising data for exploratory analysis is a major challenge in many applications. Visualisation allows scientists to gain insight into the structure and distribution of the data, for example finding common patterns and relationships between samples as well as variables. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are employed. These methods are favoured because of their simplicity, but they cannot cope with missing data and it is difficult to incorporate prior knowledge about properties of the variable space into the analysis; this is particularly important in the high-dimensional, sparse datasets typical in geochemistry. In this paper we show how to utilise a block-structured correlation matrix using a modification of a well known non-linear probabilistic visualisation model, the Generative Topographic Mapping (GTM), which can cope with missing data. The block structure supports direct modelling of strongly correlated variables. We show that including prior structural information it is possible to improve both the data visualisation and the model fit. These benefits are demonstrated on artificial data as well as a real geochemical dataset used for oil exploration, where the proposed modifications improved the missing data imputation results by 3 to 13%.

An iterative-style approach to constructing intelligent tutoring systems in mathematics

Mathematics is highly structured and also underpins most of science and engineering. For this reason, it has proved a very suitable domain for Intelligent Tutoring System (ITS) research, with the result that probably more tutoring systems have been constructed for the domain than any other. However, the literature reveals that there still exists no consensus on a credible approach or approaches for the design of such systems, despite numerous documented efforts. Current approaches to the construction of ITSs leave much to be desired. Consequently, existing ITSs in the domain suffer from a considerable number of shortcomings which render them 'unintelligent'. The thesis examines some of the reasons why this is the case. Following a critical review of existing ITSs in the domain, and some pilot studies, an alternative approach to their construction is proposed (the 'iterative-style' approach); this supports an iterative style, and also improves on at least some of the shortcomings of existing approaches. The thesis also presents an ITS for fractions which has been developed using this approach, and which has been evaluated in various ways. It has, demonstrably, improved on many of the limitations of existing ITSs; furthermore, it has been shown to be largely 'intelligent', at least more so than current tutors for the domain. Perhaps more significantly, the tutor has also been evaluated against real students with, so far, very encouraging results. The thesis thus concludes that the novel iterative-style approach is a more credible approach to the construction of ITSs in mathematics than existing techniques.

Synthesis and evaluation of polystyrene based soluble polymeric supports for organic synthesis

Several copolymers of linear polystyrene were prepared for evaluation as soluble polymeric supports for organic synthesis. These polymers were utilized for the synthesis of ?2-isoxazoline compounds. The target compounds were synthesized via 1,3-dipolar cycloaddition reactions between polymer bound alkenes and nitrile oxides generated in situ from their corresponding aldoximes. The cleaved ?2-isoxazoline compounds were tested for biological activity against Mycobacterium fortuitum. To compare the success of these linear polystyrene copolymers, some of the ?2-isoxazoline compounds synthesized on soluble polymeric supports were also prepared via traditional crosslinked polymer supports. The polymer-bound ?2-isoxazolines were also tested for antimicrobial activity. In addition attempts were made to prepare polymers containing the ?2-isoxazolines but anchored by non-hydrolysable bonds. Although the copolymers of polystyrene gave good loading capacity in mmol/g, and being soluble in chlorinated solvents it was possible to monitor the reactions by 1H NMR spectroscopy, the cleavage of the polymer bound products proved to be quite troublesome. Product purification was not as straightforward as it was anticipated. Isolation of the cleaved target compounds proved to be time consuming and laborious when compared to the traditional organic synthesis and solid phase organic synthesis (SPOS). Polymer-bound ?2-isoxazolines close to the polymer backbone exhibited some biological activity against Staphylococcus aureus. Polymers with substitution at the para-position of the aryl substituent at position 3 of isoxazoline ring showed antimicrobial activity.

Spatially structured cognitve models of semantic information:the implications for computerised databases

Existing theories of semantic cognition propose models of cognitive processing occurring in a conceptual space, where ‘meaning’ is derived from the spatial relationships between concepts’ mapped locations within the space. Information visualisation is a growing area of research within the field of information retrieval, and methods for presenting database contents visually in the form of spatial data management systems (SDMSs) are being developed. This thesis combined these two areas of research to investigate the benefits associated with employing spatial-semantic mapping (documents represented as objects in two- and three-dimensional virtual environments are proximally mapped dependent on the semantic similarity of their content) as a tool for improving retrieval performance and navigational efficiency when browsing for information within such systems. Positive effects associated with the quality of document mapping were observed; improved retrieval performance and browsing behaviour were witnessed when mapping was optimal. It was also shown using a third dimension for virtual environment (VE) presentation provides sufficient additional information regarding the semantic structure of the environment that performance is increased in comparison to using two-dimensions for mapping. A model that describes the relationship between retrieval performance and browsing behaviour was proposed on the basis of findings. Individual differences were not found to have any observable influence on retrieval performance or browsing behaviour when mapping quality was good. The findings from this work have implications for both cognitive modelling of semantic information, and for designing and testing information visualisation systems. These implications are discussed in the conclusions of this work.

Scintillation proximity assays for the real-time detection and quantification of the progress of reactions upon solid supports

A scintillation proximity assay (SPA) has been used successfully to detect and quantify, in real-time, the kinetic progress of hydrolysis of [ H]acetate esters from scintillant-containing styrenic and poly(ethylene glycol) (PEG)-based polymer supports in both organic and aqueous media.