The combination of smart hydrogels and fibre optic sensor technology for analyte detection

The subject of investigation of the present research is the use of smart hydrogels with fibre optic sensor technology. The aim was to develop a costeffective sensor platform for the detection of water in hydrocarbon media, and of dissolved inorganic analytes, namely potassium, calcium and aluminium. The fibre optic sensors in this work depend upon the use of hydrogels to either entrap chemotropic agents or to respond to external environmental changes, by changing their inherent properties, such as refractive index (RI). A review of current fibre optic technology for sensing outlined that the main principles utilised are either the measurement of signal loss or a change in wavelength of the light transmitted through the system. The signal loss principle relies on changing the conditions required for total internal reflection to occur. Hydrogels are cross-linked polymer networks that swell but do not dissolve in aqueous environments. Smart hydrogels are synthetic materials that exhibit additional properties to those inherent in their structure. In order to control the non-inherent properties, the hydrogels were fabricated with the addition of chemotropic agents. For the detection of water, hydrogels of low refractive index were synthesized using fluorinated monomers. Sulfonated monomers were used for their extreme hydrophilicity as a means of water sensing through an RI change. To enhance the sensing capability of the hydrogel, chemotropic agents, such as pH indicators and cobalt salts, were used. The system comprises of the smart hydrogel coated onto an exposed section of the fibre optic core, connected to the interrogation system measuring the difference in the signal. Information obtained was analysed using a purpose designed software. The developed sensor platform showed that an increase in the target species caused an increase in the signal lost from the sensor system, allowing for a detection of the target species. The system has potential applications in areas such as clinical point of care, water detection in fuels and the detection of dissolved ions in the water industry.

Non-standard techniques for the investigation of the visual field

The study investigated the potential applications and the limitations of non-standard techniques of visual field investigation utilizing automated perimetry. Normal subjects exhibited a greater sensitivity to kinetic stimuli than to static stimuli of identical size. The magnitude of physiological SKD was found to be largely independent of age, stimulus size, meridian and eccentricity. The absence of a dependency on stimulus size indicated that successive lateral spatial summation could not totally account for the underlying mechanism of physiological SKD. The visual field indices MD and LV exhibited a progressive deterioration during the time course of a conventional central visual field examination both for normal subjects and for ocular hypertensive patients. The fatigue effect was more pronounced in the latter stages and for the second eye tested. The confidence limits for the definition of abnormality should reflect the greater effect of fatigue on the second eye. A 330 cdm-2 yellow background was employed for blue-on-yellow perimetry. Instrument measurement range was preserved by positioning a concave mirror behind the stimulus bulb to increase the light output by 60% . The mean magnitude of SWS pathway isolation was approximately 1.4 log units relative to a 460nm stimulus filter. The absorption spectra of the ocular media exhibited an exponential increase with increase in age, whilst that of the macular pigment showed no systematic trend. The magnitude of ocular media absorption was demonstrated to reduce with increase in wavelength. Ocular media absorption was significantly greater in diabetic patients than in normal subjects. Five diabetic patients with either normal or borderline achromatic sensitivity exhibited an abnormal blue-on-yellow sensitivity; two of these patients showed no signs of retinopathy. A greater vulnerability of the SWS pathway to the diabetic disease process was hypothesized.

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.

Tactile sensing with fibre Bragg gratings and neural networks

Fibre Bragg grating sensors are usually expensive to interrogate, and part of this thesis describes a low cost interrogation system for a group of such devices which can be indefinitely scaled up for larger numbers of sensors without requiring an increasingly broadband light source. It incorporates inherent temperature correction and also uses fewer photodiodes than the number or sensors it interrogates, using neural networks to interpret the photodiode data. A novel sensing arrangement using an FBG grating encapsulated in a silicone polymer is presented. This sensor is capable of distinguishing between different surface profiles with ridges 0.5 to 1mm deep and 2mm pitch and either triangular, semicircular or square in profile. Early experiments using neural networks to distinguish between these profiles are also presented. The potential applications for tactile sensing systems incorporating fibre Bragg gratings and neural networks are explored.

A smart sensing platform for the classification of ambulatory patterns

This paper describes an innovative sensing approach allowing capture, discrimination, and classification of transients automatically in gait. A walking platform is described, which offers an alternative design to that of standard force plates with advantages that include mechanical simplicity and less restriction on dimensions. The scope of the work is to investigate as an experiment the sensitivity of the distributive tactile sensing method with the potential to address flexibility on gait assessment, including patient targeting and the extension to a variety of ambulatory applications. Using infrared sensors to measure plate deflection, gait patterns are compared with stored templates using a pattern recognition algorithm. This information is input into a neural network to classify normal and affected walking events, with a classification accuracy of just under 90 per cent achieved. The system developed has potential applications in gait analysis and rehabilitation, whereby it can be used as a tool for early diagnosis of walking disorders or to determine changes between pre- and post-operative gait.

Characterisation of femtosecond laser inscribed long period gratings in photonic crystal fibre

The use of high intensity femtosecond laser sources for inscribing fibre gratings has attained significant interest. The principal advantage of high-energy pulses is their ability for grating inscription in any material type without preprocessing or special core doping - the inscription process is controlled multi-photon absorption, void generation and subsequent local refractive index changes. The formation of grating structures in photonics crystal fibre has proven difficult, as the presence of holes within the fibre that allow wave-guidance impair and scatter the femtosecond inscription beam. Here we report on the consistent manufacture of long period gratings in endlessly single mode microstructure fibre and on their characterisation to external perturbations. Long period gratings are currently the subject of considerable research interest due to their potential applications as filters and as sensing devices, responsive to strain, temperature, bending and refractive index. Compared to the more mature fibre Bragg grating sensors, LPGs have more complex spectra, usually with broader spectral features. On the other hand they are intrinsically sensitive to bending and refractive index. Perhaps more importantly, the fibre design and choice of grating period can have a considerable influence over the sensitivity to the various parameters, for example allowing the creation of a bend sensor with minimal temperature cross-sensitivity. This control is not possible with FBG sensors. Here we compare the effects of symmetric and asymmetric femtosecond laser inscription.

Computationsl modelling of dimethyl ether separation and steam reforming in fluidized bed reactors

This study presents a computational fluid dynamic (CFD) study of Dimethyl Ether (DME) gas adsorptive separation and steam reforming (DME-SR) in a large scale Circulating Fluidized Bed (CFB) reactor. The CFD model is based on Eulerian-Eulerian dispersed flow and solved using commercial software (ANSYS FLUENT). Hydrogen is currently receiving increasing interest as an alternative source of clean energy and has high potential applications, including the transportation sector and power generation. Computational fluid dynamic (CFD) modelling has attracted considerable recognition in the engineering sector consequently leading to using it as a tool for process design and optimisation in many industrial processes. In most cases, these processes are difficult or expensive to conduct in lab scale experiments. The CFD provides a cost effective methodology to gain detailed information up to the microscopic level. The main objectives in this project are to: (i) develop a predictive model using ANSYS FLUENT (CFD) commercial code to simulate the flow hydrodynamics, mass transfer, reactions and heat transfer in a large scale dual fluidized bed system for combined gas separation and steam reforming processes (ii) implement a suitable adsorption models in the CFD code, through a user defined function, to predict selective separation of a gas from a mixture (iii) develop a model for dimethyl ether steam reforming (DME-SR) to predict hydrogen production (iv) carry out detailed parametric analysis in order to establish ideal operating conditions for future industrial application. The project has originated from a real industrial case problem in collaboration with the industrial partner Dow Corning (UK) and jointly funded by the Engineering and Physical Research Council (UK) and Dow Corning. The research examined gas separation by adsorption in a bubbling bed, as part of a dual fluidized bed system. The adsorption process was simulated based on the kinetics derived from the experimental data produced as part of a separate PhD project completed under the same fund. The kinetic model was incorporated in FLUENT CFD tool as a pseudo-first order rate equation; some of the parameters for the pseudo-first order kinetics were obtained using MATLAB. The modelling of the DME adsorption in the designed bubbling bed was performed for the first time in this project and highlights the novelty in the investigations. The simulation results were analysed to provide understanding of the flow hydrodynamic, reactor design and optimum operating condition for efficient separation. Bubbling bed validation by estimation of bed expansion and the solid and gas distribution from simulation agreed well with trends seen in the literatures. Parametric analysis on the adsorption process demonstrated that increasing fluidizing velocity reduced adsorption of DME. This is as a result of reduction in the gas residence time which appears to have much effect compared to the solid residence time. The removal efficiency of DME from the bed was found to be more than 88%. Simulation of the DME-SR in FLUENT CFD was conducted using selected kinetics from literature and implemented in the model using an in-house developed user defined function. The validation of the kinetics was achieved by simulating a case to replicate an experimental study of a laboratory scale bubbling bed by Vicente et al [1]. Good agreement was achieved for the validation of the models, which was then applied in the DME-SR in the large scale riser section of the dual fluidized bed system. This is the first study to use the selected DME-SR kinetics in a circulating fluidized bed (CFB) system and for the geometry size proposed for the project. As a result, the simulation produced the first detailed data on the spatial variation and final gas product in such an industrial scale fluidized bed system. The simulation results provided insight in the flow hydrodynamic, reactor design and optimum operating condition. The solid and gas distribution in the CFB was observed to show good agreement with literatures. The parametric analysis showed that the increase in temperature and steam to DME molar ratio increased the production of hydrogen due to the increased DME conversions, whereas the increase in the space velocity has been found to have an adverse effect. Increasing temperature between 200 oC to 350 oC increased DME conversion from 47% to 99% while hydrogen yield increased substantially from 11% to 100%. The CO2 selectivity decreased from 100% to 91% due to the water gas shift reaction favouring CO at higher temperatures. The higher conversions observed as the temperature increased was reflected on the quantity of unreacted DME and methanol concentrations in the product gas, where both decreased to very low values of 0.27 mol% and 0.46 mol% respectively at 350 °C. Increasing the steam to DME molar ratio from 4 to 7.68 increased the DME conversion from 69% to 87%, while the hydrogen yield increased from 40% to 59%. The CO2 selectivity decreased from 100% to 97%. The decrease in the space velocity from 37104 ml/g/h to 15394 ml/g/h increased the DME conversion from 87% to 100% while increasing the hydrogen yield from 59% to 87%. The parametric analysis suggests an operating condition for maximum hydrogen yield is in the region of 300 oC temperatures and Steam/DME molar ratio of 5. The analysis of the industrial sponsor’s case for the given flow and composition of the gas to be treated suggests that 88% of DME can be adsorbed from the bubbling and consequently producing 224.4t/y of hydrogen in the riser section of the dual fluidized bed system. The process also produces 1458.4t/y of CO2 and 127.9t/y of CO as part of the product gas. The developed models and parametric analysis carried out in this study provided essential guideline for future design of DME-SR at industrial level and in particular this work has been of tremendous importance for the industrial collaborator in order to draw conclusions and plan for future potential implementation of the process at an industrial scale.

Automatically Extracting Procedural Knowledge from Instructional Texts using Natural Language Processing

Procedural knowledge is the knowledge required to perform certain tasks, and forms an important part of expertise. A major source of procedural knowledge is natural language instructions. While these readable instructions have been useful learning resources for human, they are not interpretable by machines. Automatically acquiring procedural knowledge in machine interpretable formats from instructions has become an increasingly popular research topic due to their potential applications in process automation. However, it has been insufficiently addressed. This paper presents an approach and an implemented system to assist users to automatically acquire procedural knowledge in structured forms from instructions. We introduce a generic semantic representation of procedures for analysing instructions, using which natural language techniques are applied to automatically extract structured procedures from instructions. The method is evaluated in three domains to justify the generality of the proposed semantic representation as well as the effectiveness of the implemented automatic system.

A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data

In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

Bend sensors with direction recognition based on long-period gratings written in D-shaped fiber

The curvature- or bend-sensing response of long-period gratings (LPGs) UV inscribed in D-shaped fiber has been investigated experimentally. Strong fiber-orientation dependence of the spectral response when such LPGs are subjected to bending at different directions has been observed and is shown to form the basis for a new class of single-device sensor with vector-sensing capability. Potential applications utilizing the linear response and unique bend-orientation characteristics of the devices are discussed.

Two-dimensional viscoelastic discrete triangular system with negative-stiffness components

Potential applications of high-damping and high-stiffness composites have motivated extensive research on the effects of negative-stiffness inclusions on the overall properties of composites. Recent theoretical advances have been based on the Hashin-Shtrikman composite models, one-dimensional discrete viscoelastic systems and a two-dimensional nested triangular viscoelastic network. In this paper, we further analyze the two-dimensional triangular structure containing pre-selected negative-stiffness components to study its underlying deformation mechanisms and stability. Major new findings are structure-deformation evolution with respect to the magnitude of negative stiffness under shear loading and the phenomena related to dissipation-induced destabilization and inertia-induced stabilization, according to Lyapunov stability analysis. The evolution shows strong correlations between stiffness anomalies and deformation modes. Our stability results reveal that stable damping peaks, i.e. stably extreme effective damping properties, are achievable under hydrostatic loading when the inertia is greater than a critical value. Moreover, destabilization induced by elemental damping is observed with the critical inertia. Regardless of elemental damping, when the inertia is less than the critical value, a weaker system instability is identified.

Making memories available:a framework for preserving rural heritage through community knowledge management (cKM)

While most of the research in Knowledge Management (KM) has focused on business communities, there is a breadth of potential applications of KM theory and practice to wider society. This paper explores the potential of KM for rural communities, specifically for those that want to preserve their social history and collective memories (what we call heritage) to enrich the lives of others. In KM terms, this is a task of accumulating and recording knowledge (using KM techniques such as story-telling and communities of practice) to enable its retention for future use (by interested people perhaps through KM systems). We report a case study of Cardrona, a valley of approximately 120 people in New Zealand's South Island. Realising that time would erode knowledge of their community a small, motivated group of residents initiated a KM programme to create a legacy for a wider community including younger generations, tourists and scholars. This paper applies KM principles to rural communities that want to harness their collective knowledge for wider societal gain, and develops a community-based framework to inform such initiatives. As a result, we call for a wider conceptualisation of KM to include motives for managing knowledge beyond business performance to accommodate community (cKM). © 2010 Operational Research Society.

Random distributed feedback fibre lasers

The concept of random lasers exploiting multiple scattering of photons in an amplifying disordered medium in order to generate coherent light without a traditional laser resonator has attracted a great deal of attention in recent years. This research area lies at the interface of the fundamental theory of disordered systems and laser science. The idea was originally proposed in the context of astrophysics in the 1960s by V.S. Letokhov, who studied scattering with "negative absorption" of the interstellar molecular clouds. Research on random lasers has since developed into a mature experimental and theoretical field. A simple design of such lasers would be promising for potential applications. However, in traditional random lasers the properties of the output radiation are typically characterized by complex features in the spatial, spectral and time domains, making them less attractive than standard laser systems in terms of practical applications. Recently, an interesting and novel type of one-dimensional random laser that operates in a conventional telecommunication fibre without any pre-designed resonator mirrors-random distributed feedback fibre laser-was demonstrated. The positive feedback required for laser generation in random fibre lasers is provided by the Rayleigh scattering from the inhomogeneities of the refractive index that are naturally present in silica glass. In the proposed laser concept, the randomly backscattered light is amplified through the Raman effect, providing distributed gain over distances up to 100km. Although an effective reflection due to the Rayleigh scattering is extremely small (~0.1%), the lasing threshold may be exceeded when a sufficiently large distributed Raman gain is provided. Such a random distributed feedback fibre laser has a number of interesting and attractive features. The fibre waveguide geometry provides transverse confinement, and effectively one-dimensional random distributed feedback leads to the generation of a stationary near-Gaussian beam with a narrow spectrum. A random distributed feedback fibre laser has efficiency and performance that are comparable to and even exceed those of similar conventional fibre lasers. The key features of the generated radiation of random distributed feedback fibre lasers include: a stationary narrow-band continuous modeless spectrum that is free of mode competition, nonlinear power broadening, and an output beam with a Gaussian profile in the fundamental transverse mode (generated both in single mode and multi-mode fibres).This review presents the current status of research in the field of random fibre lasers and shows their potential and perspectives. We start with an introductory overview of conventional distributed feedback lasers and traditional random lasers to set the stage for discussion of random fibre lasers. We then present a theoretical analysis and experimental studies of various random fibre laser configurations, including widely tunable, multi-wavelength, narrow-band generation, and random fibre lasers operating in different spectral bands in the 1-1.6μm range. Then we discuss existing and future applications of random fibre lasers, including telecommunication and distributed long reach sensor systems. A theoretical description of random lasers is very challenging and is strongly linked with the theory of disordered systems and kinetic theory. We outline two key models governing the generation of random fibre lasers: the average power balance model and the nonlinear Schrödinger equation based model. Recently invented random distributed feedback fibre lasers represent a new and exciting field of research that brings together such diverse areas of science as laser physics, the theory of disordered systems, fibre optics and nonlinear science. Stable random generation in optical fibre opens up new possibilities for research on wave transport and localization in disordered media. We hope that this review will provide background information for research in various fields and will stimulate cross-disciplinary collaborations on random fibre lasers. © 2014 Elsevier B.V.

A fast response intrinsic humidity sensor based on an etched singlemode polymer fiber Bragg grating

A simple, low cost and fast response time intrinsic relative humidity sensor system based on an etched singlemode polymer fiber Bragg (POFBG) is presented in this paper. A macro-bend linear edge filter which converts the humidity induced wavelength shift into an intensity change is used as the interrogation technique. The singlemode POFBG is etched to micro-meters in diameter to improve the response time of the humidity sensor. A response time of 4.5 s is observed for a polymer FBG with a cladding diameter of 25 μm. The overall sensor system sensitivity was 0.23 mV/%RH. The etched POFBG humidity sensor shows anexponential decrease in response time with a decrease in fiber diameter. The developed sensor might have potential applications in a wide range of applications where fast and accurate real time humidity control is required. © 2013 Elsevier B.V. All rights reserved.

A predictor of membrane class:discriminating α-helical and β-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.