Optimisation of chromatographic separation of oxidised phospholipids and detection with targeted approaches provides greater coverage of the oxidised lipidome

Phospholipid oxidation by adventitious damage generates a wide variety of products with potentially novel biological activities that can modulate inflammatory processes associated with various diseases. To understand the biological importance of oxidised phospholipids (OxPL) and their potential role as disease biomarkers requires precise information about the abundance of these compounds in cells and tissues. There are many chemiluminescence and spectrophotometric assays available for detecting oxidised phospholipids, but they all have some limitations. Mass spectrometry coupled with liquid chromatography is a powerful and sensitive approach that can provide detailed information about the oxidative lipidome, but challenges still remain. The aim of this work is to develop improved methods for detection of OxPLs by optimisation of chromatographic separation through testing several reverse phase columns and solvent systems, and using targeted mass spectrometry approaches. Initial experiments were carried out using oxidation products generated in vitro to optimise the chromatography separation parameters and mass spectrometry parameters. We have evaluated the chromatographic separation of oxidised phosphatidylcholines (OxPCs) and oxidised phosphatidylethanolamines (OXPEs) using C8, C18 and C30 reverse phase, polystyrene – divinylbenzene based monolithic and mixed – mode hydrophilic interaction (HILIC) columns, interfaced with mass spectrometry. Our results suggest that the monolithic column was best able to separate short chain OxPCs and OxPEs from long chain oxidised and native PCs and PEs. However, variation in charge of polar head groups and extreme diversity of oxidised species make analysis of several classes of OxPLs within one analytical run impractical. We evaluated and optimised the chromatographic separation of OxPLs by serially coupling two columns: HILIC and monolith column that provided us the larger coverage of OxPL species in a single analytical run.

A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.

Gain bandwidth optimisation and enhancement in ultra-long Raman fibre laser based amplifiers

We show experimentally a 57nm gain bandwidth for an ultra-long Raman fiber laser based amplification technique using only a single pump wavelength. The enhanced gain bandwidth and gain flatness is investigated for single and multi-cavity designs. ©2010 IEEE.

FOCUS : frailty management optimisation through EIPAHA commitments and utilisation of stakeholders’ input – an innovative European project in elderly care

The goal of FOCUS, which stands for Frailty Management Optimization through EIPAHA Commitments and Utilization of Stakeholders’ Input, is to reduce the burden of frailty in Europe. The partners are working on advancing knowledge of frailty detection, assessment, and management, including biological, clinical, cognitive and psychosocial markers, in order to change the paradigm of frailty care from acute intervention to prevention. FOCUS partners are working on ways to integrate the best available evidence from frailty-related screening tools, epidemiological and interventional studies into the care of frail people and their quality of life. Frail citizens in Italy, Poland and the UK and their caregivers are being called to express their views and their experiences with treatments and interventions aimed at improving quality of life. The FOCUS Consortium is developing pathways to leverage the knowledge available and to put it in the service of frail citizens. In order to reach out to the broadest audience possible, the FOCUS Platform for Knowledge Exchange and the platform for Scaling Up are being developed with the collaboration of stakeholders. The FOCUS project is a development of the work being done by the European Innovation Partnership on Active and Healthy Ageing (EIPAHA), which aims to increase the average healthy lifespan in Europe by 2020 while fostering sustainability of health/social care systems and innovation in Europe. The knowledge and tools developed by the FOCUS project, with input from stakeholders, will be deployed to all EIPAHA participants dealing with frail older citizens to support activities and optimize performance.

Direct femtosecond laser inscription in transparent dielectrics

Since 1996 direct femtosecond inscription in transparent dielectrics has become the subject of intensive research. This enabling technology significantly expands the technological boundaries for direct fabrication of 3D structures in a wide variety of materials. It allows modification of non-photosensitive materials, which opens the door to numerous practical applications. In this work we explored the direct femtosecond inscription of waveguides and demonstrated at least one order of magnitude enhancement in the most critical parameter - the induced contrast of the refractive index in a standard borosilicate optical glass. A record high induced refractive contrast of 2.5×10-2 is demonstrated. The waveguides fabricated possess one of the lowest losses, approaching level of Fresnel reflection losses at the glassair interface. High refractive index contrast allows the fabrication of curvilinear waveguides with low bend losses. We also demonstrated the optimisation of the inscription regimes in BK7 glass over a broad range of experimental parameters and observed a counter-intuitive increase of the induced refractive index contrast with increasing translation speed of a sample. Examples of inscription in a number of transparent dielectrics hosts using high repetition rate fs laser system (both glasses and crystals) are also presented. Sub-wavelength scale periodic inscription inside any material often demands supercritical propagation regimes, when pulse peak power is more than the critical power for selffocusing, sometimes several times higher than the critical power. For a sub-critical regime, when the pulse peak power is less than the critical power for self-focusing, we derive analytic expressions for Gaussian beam focusing in the presence of Kerr non-linearity as well as for a number of other beam shapes commonly used in experiments, including astigmatic and ring-shaped ones. In the part devoted to the fabrication of periodic structures, we report on recent development of our point-by-point method, demonstrating the shortest periodic perturbation created in the bulk of a pure fused silica sample, by using third harmonics (? =267 nm) of fundamental laser frequency (? =800 nm) and 1 kHz femtosecond laser system. To overcome the fundamental limitations of the point-by-point method we suggested and experimentally demonstrated the micro-holographic inscription method, which is based on using the combination of a diffractive optical element and standard micro-objectives. Sub-500 nm periodic structures with a much higher aspect ratio were demonstrated. From the applications point of view, we demonstrate examples of photonics devices by direct femtosecond fabrication method, including various vectorial bend-sensors fabricated in standard optical fibres, as well as a highly birefringent long-period gratings by direct modulation method. To address the intrinsic limitations of femtosecond inscription at very shallow depths we suggested the hybrid mask-less lithography method. The method is based on precision ablation of a thin metal layer deposited on the surface of the sample to create a mask. After that an ion-exchange process in the melt of Ag-containing salts allows quick and low-cost fabrication of shallow waveguides and other components of integrated optics. This approach covers the gap in direct fs inscription of shallow waveguide. Perspectives and future developments of direct femtosecond micro-fabrication are also discussed.

Novel formulation strategies for the fabrication of lyophilised orally disintegrating tablets

Orally disintegrating Tablets (ODTs), also known as fast-disintegrating, fast-melt or fast-dissolving tablets, are a relatively novel dosage technology that involves the rapid disintegration or dissolution of the dosage form into a solution or suspension in the mouth without the need for water. The solution containing the active ingredients is swallowed, and the active ingredients are then absorbed through the gastrointestinal epithelium to reach the target and produce the desired effect. Formulation of ODTs was originally developed to address swallowing difficulties of conventional solid oral dosage forms (tablets and capsules) experienced by wide range of patient population, especially children and elderly. The current work investigates the formulation and development of ODTs prepared by freeze drying. Initial studies focused on formulation parameters that influence the manufacturing process and performance of lyophilised tablets based on excipients used in commercial products (gelatin and saccharides). The second phase of the work was followed up by comprehensive studies to address the essential need to create saccharide free ODTs using naturally accruing amino acids individually or in combinations. Furthermore, a factorial design study was carried out to investigate the feasibility of delivering multiparticulate systems of challenging drugs using a novel formulation that exploited the electrostatic associative interaction between gelatin and carrageenan. Finally, studies aimed to replace gelatin with ethically and morally accepted components to the end users were performed and the selected binder was used in factorial design studies to investigate and optimise ODT formulations that incorporated drugs with varies physicochemical properties. Our results show that formulation of elegant lyophilised ODTs with instant disintegration and adequate mechanical strength requires carful optimisation of gelatin concentration and bloom strength in addition to saccharide type and concentration. Successful formulation of saccharides free lyophilised ODTs requires amino acids that crystallise in the frozen state or display relatively high Tg', interact and integrate completely with the binder and, also, display short wetting time with the disintegrating medium. The use of an optimised mixture of gelatin, carrageenan and alanine was able to create viscous solutions to suspend multiparticulate systems and at the same time provide tablets with short disintegration times and adequate mechanical properties. On the other hand, gum arabic showed an outstanding potential for use as a binder in the formulation of lyophilised ODTs. Compared to gelatin formulations, the use of gum arabic simplified the formulation stages, shortened the freeze drying cycles and produced tablets with superior performance in terms of the disintegration time and mechanical strength. Furthermore, formulation of lyophilised ODTs based on gum arabic showed capability to deliver diverse range of drugs with advantages over commercial products.

The n-tuple classifier: too good to ignore

The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from the European Community StatLog project, so that the results could be compared with those reported for the 23 other algorithms the project tested. The results indicate that this ultra-fast memory-based method is a viable competitor with the others, which include optimisation-based neural network algorithms, even though the theory of memory-based neural computing is less highly developed in terms of statistical theory.

A Bayesian formulation of search, control and the exploration/exploitation trade-off

A new approach to optimisation is introduced based on a precise probabilistic statement of what is ideally required of an optimisation method. It is convenient to express the formalism in terms of the control of a stationary environment. This leads to an objective function for the controller which unifies the objectives of exploration and exploitation, thereby providing a quantitative principle for managing this trade-off. This is demonstrated using a variant of the multi-armed bandit problem. This approach opens new possibilities for optimisation algorithms, particularly by using neural network or other adaptive methods for the adaptive controller. It also opens possibilities for deepening understanding of existing methods. The realisation of these possibilities requires research into practical approximations of the exact formalism.

Topographic mappings and feed-forward neural networks

This thesis is a study of the generation of topographic mappings - dimension reducing transformations of data that preserve some element of geometric structure - with feed-forward neural networks. As an alternative to established methods, a transformational variant of Sammon's method is proposed, where the projection is effected by a radial basis function neural network. This approach is related to the statistical field of multidimensional scaling, and from that the concept of a 'subjective metric' is defined, which permits the exploitation of additional prior knowledge concerning the data in the mapping process. This then enables the generation of more appropriate feature spaces for the purposes of enhanced visualisation or subsequent classification. A comparison with established methods for feature extraction is given for data taken from the 1992 Research Assessment Exercise for higher educational institutions in the United Kingdom. This is a difficult high-dimensional dataset, and illustrates well the benefit of the new topographic technique. A generalisation of the proposed model is considered for implementation of the classical multidimensional scaling (¸mds}) routine. This is related to Oja's principal subspace neural network, whose learning rule is shown to descend the error surface of the proposed ¸mds model. Some of the technical issues concerning the design and training of topographic neural networks are investigated. It is shown that neural network models can be less sensitive to entrapment in the sub-optimal global minima that badly affect the standard Sammon algorithm, and tend to exhibit good generalisation as a result of implicit weight decay in the training process. It is further argued that for ideal structure retention, the network transformation should be perfectly smooth for all inter-data directions in input space. Finally, there is a critique of optimisation techniques for topographic mappings, and a new training algorithm is proposed. A convergence proof is given, and the method is shown to produce lower-error mappings more rapidly than previous algorithms.

Efficient training of RBF networks for classification.

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. We show how RBFs with logistic and softmax outputs can be trained efficiently using the Fisher scoring algorithm. This approach can be used with any model which consists of a generalised linear output function applied to a model which is linear in its parameters. We compare this approach with standard non-linear optimisation algorithms on a number of datasets.

Flexible Gaussian process wind field models

This technical report builds on previous reports to derive the likelihood and its derivatives for a Gaussian Process with a modified Bessel function based covariance function. The full derivation is shown. The likelihood (with gradient information) can be used in maximum likelihood procedures (i.e. gradient based optimisation) and in Hybrid Monte Carlo sampling (i.e. within a Bayesian framework).

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

Efficient training of RBF networks for classification

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. In this paper we show how RBFs with logistic and softmax outputs can be trained efficiently using algorithms derived from Generalised Linear Models. This approach is compared with standard non-linear optimisation algorithms on a number of datasets.

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

Dynamic simulation of chemical plant

A CSSL- type modular FORTRAN package, called ACES, has been developed to assist in the simulation of the dynamic behaviour of chemical plant. ACES can be harnessed, for instance, to simulate the transients in startups or after a throughput change. ACES has benefited from two existing simulators. The structure was adapted from ICL SLAM and most plant models originate in DYFLO. The latter employs sequential modularisation which is not always applicable to chemical engineering problems. A novel device of twice- round execution enables ACES to achieve general simultaneous modularisation. During the FIRST ROUND, STATE-VARIABLES are retrieved from the integrator and local calculations performed. During the SECOND ROUND, fresh derivatives are estimated and stored for simultaneous integration. ACES further includes a version of DIFSUB, a variable-step integrator capable of handling stiff differential systems. ACES is highly formalised . It does not use pseudo steady- state approximations and excludes inconsistent and arbitrary features of DYFLO. Built- in debug traps make ACES robust. ACES shows generality, flexibility, versatility and portability, and is very convenient to use. It undertakes substantial housekeeping behind the scenes and thus minimises the detailed involvement of the user. ACES provides a working set of defaults for simulation to proceed as far as possible. Built- in interfaces allow for reactions and user supplied algorithms to be incorporated . New plant models can be easily appended. Boundary- value problems and optimisation may be tackled using the RERUN feature. ACES is file oriented; a STATE can be saved in a readable form and reactivated later. Thus piecewise simulation is possible. ACES has been illustrated and verified to a large extent using some literature-based examples. Actual plant tests are desirable however to complete the verification of the library. Interaction and graphics are recommended for future work.