Investigation of healthy and infected newborn saliva: the role of proteins and lipids as potential inflammatory diagnostic tools

We have carried out a discovery proteomics investigation aimed at identifying disease biomarkers present in saliva, and, more specifically, early biomarkers of inflammation. The proteomic characterization of saliva is possible due to the straightforward and non-invasive sample collection that allows repetitive analyses for pharmacokinetic studies. These advantages are particularly relevant in the case of newborn patients. The study was carried out with samples collected during the first 48 hours of life of the newborns according to an approved Ethic Committee procedure. In particular, the salivary samples were collected from healthy and infected (n=1) newborns. Proteins were extracted through cycles of sonication, precipitated in ice cold acetone, resuspended and resolved by 2D-electrophoresis. MALDI TOF/TOF mass spectrometry analysis was performed for each spot obtaining the proteins’ identifications. Then we compared healthy newborn salivary proteome and an infected newborn salivary proteome in order to investigate proteins differently expressed in inflammatory condition. In particular the protein alpha-1-antitrypsin (A1AT), correlated with inflammation, was detected differently expressed in the infected newborn saliva. Therefore, in the second part of the project we aimed to develop a robust LC-MS based method that identifies and quantifies this inflammatory protein within saliva that might represent the first relevant step to diagnose a condition of inflammation with a no-invasive assay. The same LC-MS method is also useful to investigate the presence of the F allelic variant of the A1AT in biological samples, which is correlated with the onset of pulmonary diseases. In the last part of the work we analysed newborn saliva samples in order to investigate how phospholipids and mediators of inflammation (eicosanoids) are subject to variations under inflammatory conditions and a trend was observed in lysophosphatidylcholines composition according to the inflammatory conditions.

Ontology ranking based on the analysis of concept structures

In view of the need to provide tools to facilitate the re-use of existing knowledge structures such as ontologies, we present in this paper a system, AKTiveRank, for the ranking of ontologies. AKTiveRank uses as input the search terms provided by a knowledge engineer and, using the output of an ontology search engine, ranks the ontologies. We apply a number of metrics in an attempt to investigate their appropriateness for ranking ontologies, and compare the results with a questionnaire-based human study. Our results show that AKTiveRank will have great utility although there is potential for improvement.

A novel neural network technique for exploratory data analysis

This paper surveys the context of feature extraction by neural network approaches, and compares and contrasts their behaviour as prospective data visualisation tools in a real world problem. We also introduce and discuss a hybrid approach which allows us to control the degree of discriminatory and topographic information in the extracted feature space.

Managing healthcare quality using logical framework analysis

Purpose - The purpose of this paper is to develop an integrated quality management model that identifies problems, suggests solutions, develops a framework for implementation and helps to evaluate dynamically healthcare service performance. Design/methodology/approach - This study used the logical framework analysis (LFA) to improve the performance of healthcare service processes. LFA has three major steps - problems identification, solution derivation, and formation of a planning matrix for implementation. LFA has been applied in a case-study environment to three acute healthcare services (Operating Room utilisation, Accident and Emergency, and Intensive Care) in order to demonstrate its effectiveness. Findings - The paper finds that LFA is an effective method of quality management of hospital-based healthcare services. Research limitations/implications - This study shows LFA application in three service processes in one hospital. This very limited population sample needs to be extended. Practical implications - The proposed model can be implemented in hospital-based healthcare services in order to improve performance. It may also be applied to other services. Originality/value - Quality improvement in healthcare services is a complex and multi-dimensional task. Although various quality management tools are routinely deployed for identifying quality issues in healthcare delivery, they are not without flaws. There is an absence of an integrated approach, which can identify and analyse issues, provide solutions to resolve those issues, develop a project management framework to implement those solutions. This study introduces an integrated and uniform quality management tool for healthcare services. © Emerald Group Publishing Limited.

Strategy tools as boundary objects: a strategy-as-practice perspective

This review is structured in three sections and provides a conceptual framework for the empirical analysis of strategy tools as they are used in practice. Examples of strategy tools are SWOT analysis or Porter’s Five Forces, among others. Section one reviews empirical research into the use of strategy tools, classifying them according to variations in their use. Section two explains the concept of boundary objects as the basis for our argument that strategy tools may be understood as boundary objects. Boundary objects are artefacts that are meaningfully and usefully incorporated to enable sharing of information and transfer of knowledge across intra-organizational boundaries, such as laterally across different strategic business units or vertically across hierarchical levels. Section three draws the two bodies of literature together, conceptualizing strategy tools in practice as boundary objects. This review contributes to knowledge on using strategy tools in practice.

An evaluation of task analysis techniques for industrial process control

The concept of a task is fundamental to the discipline of ergonomics. Approaches to the analysis of tasks began in the early 1900's. These approaches have evolved and developed to the present day, when there is a vast array of methods available. Some of these methods are specific to particular contexts or applications, others more general. However, whilst many of these analyses allow tasks to be examined in detail, they do not act as tools to aid the design process or the designer. The present thesis examines the use of task analysis in a process control context, and in particular the use of task analysis to specify operator information and display requirements in such systems. The first part of the thesis examines the theoretical aspect of task analysis and presents a review of the methods, issues and concepts relating to task analysis. A review of over 80 methods of task analysis was carried out to form a basis for the development of a task analysis method to specify operator information requirements in industrial process control contexts. Of the methods reviewed Hierarchical Task Analysis was selected to provide such a basis and developed to meet the criteria outlined for such a method of task analysis. The second section outlines the practical application and evolution of the developed task analysis method. Four case studies were used to examine the method in an empirical context. The case studies represent a range of plant contexts and types, both complex and more simple, batch and continuous and high risk and low risk processes. The theoretical and empirical issues are drawn together and a method developed to provide a task analysis technique to specify operator information requirements and to provide the first stages of a tool to aid the design of VDU displays for process control.

The influence of tool geometry on the performance of drilling tools

The main objective of the work presented in this thesis is to investigate the two sides of the flute, the face and the heel of a twist drill. The flute face was designed to yield straight diametral lips which could be extended to eliminate the chisel edge, and consequently a single cutting edge will be obtained. Since drill rigidity and space for chip conveyance have to be a compromise a theoretical expression is deduced which enables optimum chip disposal capacity to be described in terms of drill parameters. This expression is used to describe the flute heel side. Another main objective is to study the effect on drill performance of changing the conventional drill flute. Drills were manufactured according to the new flute design. Tests were run in order to compare the performance of a conventional flute drill and non conventional design put forward. The results showed that 50% reduction in thrust force and approximately 18% reduction in torque were attained for the new design. The flank wear was measured at the outer corner and found to be less for the new design drill than for the conventional one in the majority of cases. Hole quality, roundness, size and roughness were also considered as a further aspect of drill performance. Improvement in hole quality is shown to arise under certain cutting conditions. Accordingly it might be possible to use a hole which is produced in one pass of the new drill which previously would have required a drilled and reamed hole. A subsidiary objective is to design the form milling cutter that should be employed for milling the foregoing special flute from drill blank allowing for the interference effect. A mathematical analysis in conjunction with computing technique and computers is used. To control the grinding parameter, a prototype drill grinder was designed and built upon the framework of an existing cincinnati cutter grinder. The design and build of the new grinder is based on a computer aided drill point geometry analysis. In addition to the conical grinding concept, the new grinder is also used to produce spherical point utilizing a computer aided drill point geometry analysis.

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

Optimising the clinical analysis of retinal image quality in the human eye

Visual perception is dependent on both light transmission through the eye and neuronal conduction through the visual pathway. Advances in clinical diagnostics and treatment modalities over recent years have increased the opportunities to improve the optical path and retinal image quality. Higher order aberrations and retinal straylight are two major factors that influence light transmission through the eye and ultimately, visual outcome. Recent technological advancements have brought these important factors into the clinical domain, however the potential applications of these tools and considerations regarding interpretation of data are much underestimated. The purpose of this thesis was to validate and optimise wavefront analysers and a new clinical tool for the objective evaluation of intraocular scatter. The application of these methods in a clinical setting involving a range of conditions was also explored. The work was divided into two principal sections: 1. Wavefront Aberrometry: optimisation, validation and clinical application The main findings of this work were: • Observer manipulation of the aberrometer increases variability by a factor of 3. • Ocular misalignment can profoundly affect reliability, notably for off-axis aberrations. • Aberrations measured with wavefront analysers using different principles are not interchangeable, with poor relationships and significant differences between values. • Instrument myopia of around 0.30D is induced when performing wavefront analysis in non-cyclopleged eyes; values can be as high as 3D, being higher as the baseline level of myopia decreases. Associated accommodation changes may result in relevant changes to the aberration profile, particularly with respect to spherical aberration. • Young adult healthy Caucasian eyes have significantly more spherical aberration than Asian eyes when matched for age, gender, axial length and refractive error. Axial length is significantly correlated with most components of the aberration profile. 2. Intraocular light scatter: Evaluation of subjective measures and validation and application of a new objective method utilising clinically derived wavefront patterns. The main findings of this work were: • Subjective measures of clinical straylight are highly repeatable. Three measurements are suggested as the optimum number for increased reliability. • Significant differences in straylight values were found for contact lenses designed for contrast enhancement compared to clear lenses of the same design and material specifications. Specifically, grey/green tints induced significantly higher values of retinal straylight. • Wavefront patterns from a commercial Hartmann-Shack device can be used to obtain objective measures of scatter and are well correlated with subjective straylight values. • Perceived retinal stray light was similar in groups of patients implanted with monofocal and multi focal intraocular lenses. Correlation between objective and subjective measurements of scatter is poor, possibly due to different illumination conditions between the testing procedures, or a neural component which may alter with age. Careful acquisition results in highly reproducible in vivo measures of higher order aberrations; however, data from different devices are not interchangeable which brings the accuracy of measurement into question. Objective measures of intraocular straylight can be derived from clinical aberrometry and may be of great diagnostic and management importance in the future.

Police interviews with women reporting rape: a critical discourse analysis

This study investigates the discursive patterns of interactions between police interviewers and women reporting rape in significant witness interviews. Data in the form of video recorded interviews were obtained from a UK police force for the purposes of this study. The data are analysed using a multi-method approach, incorporating tools from micro-sociology, Conversation Analysis and Discursive Psychology, to reveal patterns of interactional control, negotiation, and interpretation. The study adopts a critical approach, which is to say that as well as describing discursive patterns, it explains them in light of the discourse processes involved in the production and consumption of police interview talk, and comments on the relationship between these discourse processes and the social context in which they occur. A central focus of the study is how interviewers draw on particular interactional resources to shape interviewees? accounts in particular ways, and this is discussed in relation to the institutional role of the significant witness interview. The discussion is also extended to the ways in which mainstream rape ideology is both reflected in, and maintained by, the discursive choices of participants. The findings of this study indicate that there are a number of issues to be addressed in terms of the training currently offered to officers at Level 2 of the Professionalising Investigation Programme (PIP) (NPIA, 2009) who intend to conduct significant witness interviews. Furthermore, a need is identified to bring the linguistic and discursive processes of negotiation and transformation identified by the study to the attention of the justice system as a whole. This is a particularly pressing need in light of judicial reluctance to replace written witness statements, the current „end product? of significant witness interviews, with the video recorded interview in place of direct examination in cases of rape.

Numerical and statistical analysis of long-haul undersea optical communication systems

Firstly, we numerically model a practical 20 Gb/s undersea configuration employing the Return-to-Zero Differential Phase Shift Keying data format. The modelling is completed using the Split-Step Fourier Method to solve the Generalised Nonlinear Schrdinger Equation. We optimise the dispersion map and per-channel launch power of these channels and investigate how the choice of pre/post compensation can influence the performance. After obtaining these optimal configurations, we investigate the Bit Error Rate estimation of these systems and we see that estimation based on Gaussian electrical current systems is appropriate for systems of this type, indicating quasi-linear behaviour. The introduction of narrower pulses due to the deployment of quasi-linear transmission decreases the tolerance to chromatic dispersion and intra-channel nonlinearity. We used tools from Mathematical Statistics to study the behaviour of these channels in order to develop new methods to estimate Bit Error Rate. In the final section, we consider the estimation of Eye Closure Penalty, a popular measure of signal distortion. Using a numerical example and assuming the symmetry of eye closure, we see that we can simply estimate Eye Closure Penalty using Gaussian statistics. We also see that the statistics of the logical ones dominates the statistics of the logical ones dominates the statistics of signal distortion in the case of Return-to-Zero On-Off Keying configurations.

Stabilising cysteinyl thiol oxidation and nitrosation for proteomic analysis

Oxidation and S-nitrosylation of cysteinyl thiols (Cys-SH) to sulfenic (Cys-SOH), sulfinic (Cys-SO2H), sulfonic acids (Cys-SO3H), disulphides and S-nitrosothiols are suggested as important post-translational modifications that can activate or deactivate the function of many proteins. Non-enzymatic post-translational modifications to cysteinyl thiols have been implicated in a wide variety of physiological and pathophysiological states but have been difficult to monitor in a physiological setting because of a lack of experimental tools. The purpose of this review is to bring together the approaches that have been developed for stably trapping cysteine either in its reduced or oxidised forms for enrichment and or subsequent mass spectrometric analysis. These tools are providing insight into potential targets for post-translational modifications to cysteine modification in vivo. This article is part of a Special Issue entitled: Special Issue: Posttranslational Protein modifications in biology and Medicine. © 2013.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

Selection of simulation tools for improving supply chain performance

Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach.

IT as enabler of sustainable farming:an empirical analysis of farmers' adoption decision of precision agriculture technology

Precision agriculture (PA) describes a suite of IT based tools which allow farmers to electronically monitor soil and crop conditions and analyze treatment options. This study tests a model explaining the difficulties of PA technology adoption. The model draws on theories of technology acceptance and diffusion of innovation and is validated using survey data from farms in Canada. Findings highlight the importance of compatibility among PA technology components and the crucial role of farmers' expertise. The model provides the theoretical and empirical basis for developing policies and initiatives to support PA technology adoption.