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Applications of LC-MS metabolomic profiling in inflammatory bowel disease and the development of derivatisation methods to enhance selective detection of certain compound classes
Get PDFInflammatory bowel disease (IBD) is a chronic inflammation of all parts of the gastrointestinal tract and is represented by two major variations, ulcerative colitis (UC) and Crohn's disease (CD). It is diagnosed based on the pattern of inflammation. In order to understand the pathology of the disease better urine and saliva samples were collected from patients with IBD, patients in remission and a control group. The metabolomes of the urine and saliva samples were profiled by carrying out chromatography on a ZICpHILIC column in combination with high resolution mass spectrometry.;It was possible to separate the different classes of urine samples on the basis of their metabolomic profiles by modelling with data using orthogonal partial least squares analysis (OPLSDA). A number of metabolites were found to vary between the three groups although the models for separation were weak. The OPLSDA models of the saliva data were much stronger and saliva analysis looks promising for diagnostic and prognostic purposes. Nine variables were able to discriminate the control and affected samples and these included four sphingosine bases.;The analysis of short chain fatty acids (SCFAs) by LC-MS is a problem since they are too volatile to give good responses. SCFAs are potentially important makers for IBD. A quantitative LC-MS method for acetic, propionic, butyric and lactic acids was developed by carrying out derivatisation of the acids using a carbodimide to activate the acids and then reacting with dimethylaminophenylamine and separating the derivatives using HILIC chromatography. Quantification was carried out by using stable isotope dilution. The method was very sensitive but detection limits were set by the background contamination by the SCFAs rather than by absolute sensitivity.;The method was applied to the urine samples and differences in acetate and butyrate were found between the affected and control samples. The microbiome plays a role in IBD and one marker for bacterial activity it the breakdown of dietary fibre in sugar monomers. Thus urine and saliva samples from controls and IBD samples were profiled using a reductive amination method previously developed. It was found that there were significant differences in the pattern of hexoses, pentoses and deoxy hexoses in the urine and saliva samples.Inflammatory bowel disease (IBD) is a chronic inflammation of all parts of the gastrointestinal tract and is represented by two major variations, ulcerative colitis (UC) and Crohn's disease (CD). It is diagnosed based on the pattern of inflammation. In order to understand the pathology of the disease better urine and saliva samples were collected from patients with IBD, patients in remission and a control group. The metabolomes of the urine and saliva samples were profiled by carrying out chromatography on a ZICpHILIC column in combination with high resolution mass spectrometry.;It was possible to separate the different classes of urine samples on the basis of their metabolomic profiles by modelling with data using orthogonal partial least squares analysis (OPLSDA). A number of metabolites were found to vary between the three groups although the models for separation were weak. The OPLSDA models of the saliva data were much stronger and saliva analysis looks promising for diagnostic and prognostic purposes. Nine variables were able to discriminate the control and affected samples and these included four sphingosine bases.;The analysis of short chain fatty acids (SCFAs) by LC-MS is a problem since they are too volatile to give good responses. SCFAs are potentially important makers for IBD. A quantitative LC-MS method for acetic, propionic, butyric and lactic acids was developed by carrying out derivatisation of the acids using a carbodimide to activate the acids and then reacting with dimethylaminophenylamine and separating the derivatives using HILIC chromatography. Quantification was carried out by using stable isotope dilution. The method was very sensitive but detection limits were set by the background contamination by the SCFAs rather than by absolute sensitivity.;The method was applied to the urine samples and differences in acetate and butyrate were found between the affected and control samples. The microbiome plays a role in IBD and one marker for bacterial activity it the breakdown of dietary fibre in sugar monomers. Thus urine and saliva samples from controls and IBD samples were profiled using a reductive amination method previously developed. It was found that there were significant differences in the pattern of hexoses, pentoses and deoxy hexoses in the urine and saliva samples
Localisation of Bose-Einstein condensates in optical lattices
Get PDFThe properties of Bose-Einstein condensates can be studied and controlled effectively when trapped in optical lattices formed by two counter-propagating laser beams. The dynamics of Bose-Einstein condensates in optical lattices are well-described by a continuous model using the Gross-Pitaevskii equation in a modulated potential or, in the case of deep potentials, a discrete model using the Discrete Nonlinear Schrodinger equation. Spatially localised modes, known as lattice solitons in the continuous model, or discrete breathers in the discrete model, can occur and are the focus of this thesis. Theoretical and computational studies of these localised modes are investigated in three different situations. Firstly, a model of a Bose-Einstein condensate in a ring optical lattice with atomic dissipations applied at a stationary or at a moving location on the ring is presented in the continuous model. The localised dissipation is shown to generate and stabilise both stationary and traveling lattice solitons. The solutions generated include spatially stationary quasiperiodic lattice solitons and a family of traveling lattice solitons with two intensity peaks per potential well with no counterpart in the discrete case. Collisions between traveling and stationary lattice solitons as well as between two traveling lattice solitons display a dependence on the lattice depth. Then, collisions with a potential barrier of either travelling lattice solitons or travelling discrete breathers are investigated along with their dependence on the height of the barrier. Regions of complete reection or of partial reflection where the incoming soliton/breather is split in two, are observed and understood interms of the soliton properties. Partial trapping of the atoms in the barrier is observed for positive barrier heights due to the negative effective mass of the solitons/breathers. Finally, two coupled discrete nonlinear Schrodinger equations can describe the interaction and collisions of breathers in two-species Bose-Einstein condensates in deep optical lattices. This is done for two cases of experimental relevance: a mixture of two ytterbium isotopes and a mixture of Rubidium (87Rb) and Potassium(41K) atoms. Depending on their initial separation, interaction between stationary breathers of different species can lead to the formation of symbiotic localised structures or transform one of the breathers from a stationary one into a travelling one. Collisions between travelling and stationary discrete breathers composed of different species are separated in four distinct regimes ranging from totally elastic when the interspecies interaction is highly attractive to mutual destruction when the interaction is suffciently large and repulsive.The properties of Bose-Einstein condensates can be studied and controlled effectively when trapped in optical lattices formed by two counter-propagating laser beams. The dynamics of Bose-Einstein condensates in optical lattices are well-described by a continuous model using the Gross-Pitaevskii equation in a modulated potential or, in the case of deep potentials, a discrete model using the Discrete Nonlinear Schrodinger equation. Spatially localised modes, known as lattice solitons in the continuous model, or discrete breathers in the discrete model, can occur and are the focus of this thesis. Theoretical and computational studies of these localised modes are investigated in three different situations. Firstly, a model of a Bose-Einstein condensate in a ring optical lattice with atomic dissipations applied at a stationary or at a moving location on the ring is presented in the continuous model. The localised dissipation is shown to generate and stabilise both stationary and traveling lattice solitons. The solutions generated include spatially stationary quasiperiodic lattice solitons and a family of traveling lattice solitons with two intensity peaks per potential well with no counterpart in the discrete case. Collisions between traveling and stationary lattice solitons as well as between two traveling lattice solitons display a dependence on the lattice depth. Then, collisions with a potential barrier of either travelling lattice solitons or travelling discrete breathers are investigated along with their dependence on the height of the barrier. Regions of complete reection or of partial reflection where the incoming soliton/breather is split in two, are observed and understood interms of the soliton properties. Partial trapping of the atoms in the barrier is observed for positive barrier heights due to the negative effective mass of the solitons/breathers. Finally, two coupled discrete nonlinear Schrodinger equations can describe the interaction and collisions of breathers in two-species Bose-Einstein condensates in deep optical lattices. This is done for two cases of experimental relevance: a mixture of two ytterbium isotopes and a mixture of Rubidium (87Rb) and Potassium(41K) atoms. Depending on their initial separation, interaction between stationary breathers of different species can lead to the formation of symbiotic localised structures or transform one of the breathers from a stationary one into a travelling one. Collisions between travelling and stationary discrete breathers composed of different species are separated in four distinct regimes ranging from totally elastic when the interspecies interaction is highly attractive to mutual destruction when the interaction is suffciently large and repulsive
A multi-agent system design and implementation for flexible network management
Get PDFStrathclyde theses - ask staff. Thesis no. : T14887With the introduction of renewable energy technologies to reduce greenhouse gas emissions, a significant amount of Distributed Generation (DG) has connected to distribution networks. Hence, the operation of electrical power distribution systems has become complicated and increasingly challenging due to the uncertainty of bi-directional power flow, voltage fluctuations, and frequency deviations. To help manage these issues, the system requires more intelligent functions and flexibility in order to support solutions for network management and operation. Moreover, distribution network operators are looking for an active approach to maximise the utilisation of network capacity while solving network issues for more DG connections. As a result, Active Network Management (ANM) has been proposed to facilitate DG connections without breaching network operation limits. This is achieved by managing network control functions in line with operational objectives and it is often seen as a way to avoiding the high costs of reinforcing the existing infrastructure. However, as the network continues to change, such as increasing DG connections, and control functions keep evolving overtime. ANM is considered to be part of the solution for at least the medium term.;ANM is considered to be part of the solution for at least the medium term. Therefore, ANM requires sufficient flexibility to adapt changes to its environment and extensibility to upgrade control functions overtime for future needs. A key aspect of this is interoperability to allow ANM to interact with different control devices, such as intelligent electronic devices, to collect data and realise control purposes as they also evolve.Multi-agent Systems (MAS) is one of the most relevant technologies to address the above challenges as it provides autonomous and proactive behaviour in open and dynamic environments, which is analogous to new DG connections. In addition, MAS offers a flexible and extensible platform that is the advantage of other relevant technologies, such as a service-oriented architecture. Therefore, it is proposed as part of the work of this thesis that the requirement for flexibility and extensibility can be achieved through the development of control functions as intelligent agents with scalable capabilities brought about through the use of MAS technology. The novel solver agent developed as part of the work of this thesis is an essentialcomponent of the MAS architecture considered in this thesis incorporates an integrated control algorithm and negotiation capability to solve conflicts between various control solutions.;This thesis presents a fully integrated MAS architecture for ANM. It is developed by following a comprehensive design methodology and each stage of the proposed MAS architecture is detailed through specification to implementation. Selected control algorithms are developed as intelligent agents to achieve multiple ANM solutions. In order to provide a common understanding of terminology for agent communications, ontologies for power system control applications, including thermal overload and voltage violation, have been created. A novel IEC 61850 interface has been developed and embedded inside the agent to address interoperability issue between devices for data collection and control.;To evaluate the performance of the developed MAS architecture, along with the novel elements of this thesis a range of simulation case studies are explored. Studies are based on a closed-loop simulation environment with a power system simulator: one case study is based on an operational UK 11 kV radial distribution network to demonstrate the application of MAS for various power system controls; another examines the self-organising ability of the developed MAS architecture by using the ε decomposition algorithm for distributed voltage regulation. The results demonstrate the flexibility, extensibility, and self-organisation capabilities of the novel fully integrated MAS architecture. This is built upon and the prospects for the inclusion of the MAS technology within operational power systems is discussed and recommendations made as part of this thesis.With the introduction of renewable energy technologies to reduce greenhouse gas emissions, a significant amount of Distributed Generation (DG) has connected to distribution networks. Hence, the operation of electrical power distribution systems has become complicated and increasingly challenging due to the uncertainty of bi-directional power flow, voltage fluctuations, and frequency deviations. To help manage these issues, the system requires more intelligent functions and flexibility in order to support solutions for network management and operation. Moreover, distribution network operators are looking for an active approach to maximise the utilisation of network capacity while solving network issues for more DG connections. As a result, Active Network Management (ANM) has been proposed to facilitate DG connections without breaching network operation limits. This is achieved by managing network control functions in line with operational objectives and it is often seen as a way to avoiding the high costs of reinforcing the existing infrastructure. However, as the network continues to change, such as increasing DG connections, and control functions keep evolving overtime. ANM is considered to be part of the solution for at least the medium term.;ANM is considered to be part of the solution for at least the medium term. Therefore, ANM requires sufficient flexibility to adapt changes to its environment and extensibility to upgrade control functions overtime for future needs. A key aspect of this is interoperability to allow ANM to interact with different control devices, such as intelligent electronic devices, to collect data and realise control purposes as they also evolve.Multi-agent Systems (MAS) is one of the most relevant technologies to address the above challenges as it provides autonomous and proactive behaviour in open and dynamic environments, which is analogous to new DG connections. In addition, MAS offers a flexible and extensible platform that is the advantage of other relevant technologies, such as a service-oriented architecture. Therefore, it is proposed as part of the work of this thesis that the requirement for flexibility and extensibility can be achieved through the development of control functions as intelligent agents with scalable capabilities brought about through the use of MAS technology. The novel solver agent developed as part of the work of this thesis is an essentialcomponent of the MAS architecture considered in this thesis incorporates an integrated control algorithm and negotiation capability to solve conflicts between various control solutions.;This thesis presents a fully integrated MAS architecture for ANM. It is developed by following a comprehensive design methodology and each stage of the proposed MAS architecture is detailed through specification to implementation. Selected control algorithms are developed as intelligent agents to achieve multiple ANM solutions. In order to provide a common understanding of terminology for agent communications, ontologies for power system control applications, including thermal overload and voltage violation, have been created. A novel IEC 61850 interface has been developed and embedded inside the agent to address interoperability issue between devices for data collection and control.;To evaluate the performance of the developed MAS architecture, along with the novel elements of this thesis a range of simulation case studies are explored. Studies are based on a closed-loop simulation environment with a power system simulator: one case study is based on an operational UK 11 kV radial distribution network to demonstrate the application of MAS for various power system controls; another examines the self-organising ability of the developed MAS architecture by using the ε decomposition algorithm for distributed voltage regulation. The results demonstrate the flexibility, extensibility, and self-organisation capabilities of the novel fully integrated MAS architecture. This is built upon and the prospects for the inclusion of the MAS technology within operational power systems is discussed and recommendations made as part of this thesis
A numerical & experimental investigation into size effects within loaded additively manufactured cellular solids
Get PDFThe behaviour of heterogeneous materials when loaded cannot be adequately described by classical elasticity as it doesn't account for the presence of internal length-scales. Higher order theories such as micropolar elasticity may be more appropriate, though the additional elastic constants required to fully describe such materials are hard to identify experimentally. In micropolar theory a size effect is predicted in bending and torsion which is revealed as an increase in relative stiffness with decreasing size at scales approaching the cellular microstructure. Thus, at the microstructural level, size and scale becomes an important consideration. Hence, materials which appear homogeneous at a large scale may be heterogeneous at smaller scales when overall size approaches that of the cellular structure. Addressing this issue requires aclear understanding of how scale influences the material's mechanical properties. Here, the mechanical response of periodic, cellular lattices has been explored within the context of micropolar theory by conducting discrete numerical simulations and experimental tests. It will be shown that the size effects displayed in bending and torsion are strongly dependent on the cellular volume fraction and sample section second moment of area associated with the distribution of the matrix material within the cells comprising the section. Crucially however, these effects may be masked by surface texture and localised loading conditions. Despite the inherent difficulties associated with experimental testing, the size effects which are predicted by micropolar theory are identified experimentally in an additively manufactured cellular material. The observed size effects showed reasonable agreement to numerical simulations performed in ANSYS. Demonstrating that the behaviour of structured cellular materials with deterministic properties, fabricated by additive manufacturing, can be described by more generalised deformation theories is important as it enables the design and development of new and novel materials to be explored and exploited in lightweight structural applications.The behaviour of heterogeneous materials when loaded cannot be adequately described by classical elasticity as it doesn't account for the presence of internal length-scales. Higher order theories such as micropolar elasticity may be more appropriate, though the additional elastic constants required to fully describe such materials are hard to identify experimentally. In micropolar theory a size effect is predicted in bending and torsion which is revealed as an increase in relative stiffness with decreasing size at scales approaching the cellular microstructure. Thus, at the microstructural level, size and scale becomes an important consideration. Hence, materials which appear homogeneous at a large scale may be heterogeneous at smaller scales when overall size approaches that of the cellular structure. Addressing this issue requires aclear understanding of how scale influences the material's mechanical properties. Here, the mechanical response of periodic, cellular lattices has been explored within the context of micropolar theory by conducting discrete numerical simulations and experimental tests. It will be shown that the size effects displayed in bending and torsion are strongly dependent on the cellular volume fraction and sample section second moment of area associated with the distribution of the matrix material within the cells comprising the section. Crucially however, these effects may be masked by surface texture and localised loading conditions. Despite the inherent difficulties associated with experimental testing, the size effects which are predicted by micropolar theory are identified experimentally in an additively manufactured cellular material. The observed size effects showed reasonable agreement to numerical simulations performed in ANSYS. Demonstrating that the behaviour of structured cellular materials with deterministic properties, fabricated by additive manufacturing, can be described by more generalised deformation theories is important as it enables the design and development of new and novel materials to be explored and exploited in lightweight structural applications
High bandwidth neural interfacing using visible light communication
No full textThe sheer amount of information being processed arising from the high-density network of nerve cells in the brain, imposes severe restrictions with respect to the number of neurons that can be observed simultaneously. Many techniques focus on smaller nerve cell populations, and introduce wired electrode interfaces directly contacting neural tissue. These tethered methods however can lead to a host of detrimental issues, such as movement restriction affecting behaviour, and infections at the interface site. Due to this, devices capable of wirelessly transmitting large amounts of neural data are needed. To correlate neuron activity with behaviour, such devices are inserted into various animal models, preferably in vivo. The mouse model is particularly popular because of the familiarity of its genetics, physiology, and low upkeep costs. With the advent of such techniques as optogenetics, which allow increasingly precise light mediated activation of nerve cells, the preference for mice was further reinforced where they are the primary animal of choice. However, the majority of currently available wireless devices are too big and heavy to allow the freely moving behaviour of mice. Most of these use the RF based data transmission, and use larger energy storage units to supply the power required for higher data rates. The size limitations also restrict the maximum dimensions for an antenna that ca be used, further restricting the maximum available bandwidth. To propose a solution to these issues, the thesis outlines the design of low power devices that use visible light communication (VLC) to transmit neural data. As a pathway towards a fully wireless in vivo device we first develop an in vitro system, and interfaced with a 61-channel array containing rodent retinal tissue. The device was validated by sending neural data through the optical link, using an off the shelf LED. A fully wireless in vivo package was then developed. It was verified with test signals in a simulated environment, and a head fixed mouse at transmission distance of 20 cm. During in vivo recording, neural activity was stimulated using optogenetic techniques. The developed wireless system transmits 32 channels of uncompressed data (10.24 Mbps) in a 5g package. Strategies to transition to freely moving experiments and scale up channel count will be discussed. Finally, methods to readily reduce the weight will be outlined.The sheer amount of information being processed arising from the high-density network of nerve cells in the brain, imposes severe restrictions with respect to the number of neurons that can be observed simultaneously. Many techniques focus on smaller nerve cell populations, and introduce wired electrode interfaces directly contacting neural tissue. These tethered methods however can lead to a host of detrimental issues, such as movement restriction affecting behaviour, and infections at the interface site. Due to this, devices capable of wirelessly transmitting large amounts of neural data are needed. To correlate neuron activity with behaviour, such devices are inserted into various animal models, preferably in vivo. The mouse model is particularly popular because of the familiarity of its genetics, physiology, and low upkeep costs. With the advent of such techniques as optogenetics, which allow increasingly precise light mediated activation of nerve cells, the preference for mice was further reinforced where they are the primary animal of choice. However, the majority of currently available wireless devices are too big and heavy to allow the freely moving behaviour of mice. Most of these use the RF based data transmission, and use larger energy storage units to supply the power required for higher data rates. The size limitations also restrict the maximum dimensions for an antenna that ca be used, further restricting the maximum available bandwidth. To propose a solution to these issues, the thesis outlines the design of low power devices that use visible light communication (VLC) to transmit neural data. As a pathway towards a fully wireless in vivo device we first develop an in vitro system, and interfaced with a 61-channel array containing rodent retinal tissue. The device was validated by sending neural data through the optical link, using an off the shelf LED. A fully wireless in vivo package was then developed. It was verified with test signals in a simulated environment, and a head fixed mouse at transmission distance of 20 cm. During in vivo recording, neural activity was stimulated using optogenetic techniques. The developed wireless system transmits 32 channels of uncompressed data (10.24 Mbps) in a 5g package. Strategies to transition to freely moving experiments and scale up channel count will be discussed. Finally, methods to readily reduce the weight will be outlined
Mitigating size related limitations in wind turbine control
Get PDFAs the size of wind turbines steadily increase, a control system which can manage the loads and dynamics becomes more important. In this thesis, the effects of turbine scale on the control system are examined and designs which mitigate the arising problems are presented and discussed.;In this thesis, a set of three wind turbines is developed using a method to scale a mathematical model of a wind turbine while maintaining similarity in the dynamics. This framework for producing the scaled wind turbines is presented and discussed.;The performance of the controller for a very large wind turbine is limited by the dynamics of the tower. By accounting for the non-minimum-phase dynamics present in the wind turbine, previous work has reduced loads in the tower. In this thesis, this framework is developed to improve speed and power control and recover some of the performance lost as turbine size increases.;As well as the effect of the tower, non-linear dynamics present in the pitch control loop adversely effect performance. Previous work has developed a framework for a controller for non-linear plants which satisfies a criteria called extended local linear equivalence (ELLE). A novel controller which satisfies the ELLE criteria is presented which counters the non-linear dynamics present in the wind turbine and reduces fluctuations in speed and power.;A comparison of a baseline controller and a controller which incorporates the two designs described above shows significant reductions in the fluctuations of rotor and generator speed as well as power output. These changes to the controller also show greater improvements to performance in larger turbines. The inuence of the the tower and the non-linear dynamics present in the aerodynamics both become more severe as the size of the wind turbine increases. Therefore, a controller design which mitigates these effects has greater value as the wind energy industry continues on its path and develops ever larger wind turbines.As the size of wind turbines steadily increase, a control system which can manage the loads and dynamics becomes more important. In this thesis, the effects of turbine scale on the control system are examined and designs which mitigate the arising problems are presented and discussed.;In this thesis, a set of three wind turbines is developed using a method to scale a mathematical model of a wind turbine while maintaining similarity in the dynamics. This framework for producing the scaled wind turbines is presented and discussed.;The performance of the controller for a very large wind turbine is limited by the dynamics of the tower. By accounting for the non-minimum-phase dynamics present in the wind turbine, previous work has reduced loads in the tower. In this thesis, this framework is developed to improve speed and power control and recover some of the performance lost as turbine size increases.;As well as the effect of the tower, non-linear dynamics present in the pitch control loop adversely effect performance. Previous work has developed a framework for a controller for non-linear plants which satisfies a criteria called extended local linear equivalence (ELLE). A novel controller which satisfies the ELLE criteria is presented which counters the non-linear dynamics present in the wind turbine and reduces fluctuations in speed and power.;A comparison of a baseline controller and a controller which incorporates the two designs described above shows significant reductions in the fluctuations of rotor and generator speed as well as power output. These changes to the controller also show greater improvements to performance in larger turbines. The inuence of the the tower and the non-linear dynamics present in the aerodynamics both become more severe as the size of the wind turbine increases. Therefore, a controller design which mitigates these effects has greater value as the wind energy industry continues on its path and develops ever larger wind turbines
Computationally guided rational ligand design of novel iridium (I) complexes for elevated substrate applicability in hydrogen isotope exchange processes
Get PDFUsing a computationally guided rational ligand design approach, a novel chelated NHC-P iridium(I) catalyst system has been identified for the directed hydrogen isotope exchange (HIE) of aryl sulfones. The catalyst design process was aided primarily through DFT binding energy calculations. The solvent scope of the reaction was studied, and the optimised conditions applied to the successful deuterium labelling of a broad range of 20 aryl sulfones. The catalyst system was also shown to be highly active in the HIE of aryl sulfones at sub-atmospheric pressures of deuterium. Additionally, the catalyst system was applied in the tritiation of aryl sulfones, affording tritiated samples of methylphenyl sulfone, as well as a GPR119 agonist, in high levels of specific activity.This chelated catalyst system was then further refined for the labelling of highly substituted sulfonamides. A more focussed approach to the catalyst design process was taken at this stage, with a combination of binding energy calculations and binding mode analysis being used to guide the modification of the ligand. This resulted in a novel, chelated NHC-Py system, which proved to be highly active in the HIE of a broad range of highly substituted sulfonamides. A total of 22 sulfonamide substrates were synthesised, and labelled using this novel catalyst system. Additionally, this complex was shown to be highly effective in the deuteration of sulfoximines, for which the means of labelling are severely under met.Finally, our studies in the labelling of aryl sulfones led us to the serendipitous discovery of ether-directed HIE. This process was investigated with our novel NHC-P catalyst system, and a substrate scope established. Additionally, a potential application in form of labelling natural products, and natural product-like molecules has been proposed, with a series of three natural product-like molecules having been synthesised for attempts towards labelling.Using a computationally guided rational ligand design approach, a novel chelated NHC-P iridium(I) catalyst system has been identified for the directed hydrogen isotope exchange (HIE) of aryl sulfones. The catalyst design process was aided primarily through DFT binding energy calculations. The solvent scope of the reaction was studied, and the optimised conditions applied to the successful deuterium labelling of a broad range of 20 aryl sulfones. The catalyst system was also shown to be highly active in the HIE of aryl sulfones at sub-atmospheric pressures of deuterium. Additionally, the catalyst system was applied in the tritiation of aryl sulfones, affording tritiated samples of methylphenyl sulfone, as well as a GPR119 agonist, in high levels of specific activity.This chelated catalyst system was then further refined for the labelling of highly substituted sulfonamides. A more focussed approach to the catalyst design process was taken at this stage, with a combination of binding energy calculations and binding mode analysis being used to guide the modification of the ligand. This resulted in a novel, chelated NHC-Py system, which proved to be highly active in the HIE of a broad range of highly substituted sulfonamides. A total of 22 sulfonamide substrates were synthesised, and labelled using this novel catalyst system. Additionally, this complex was shown to be highly effective in the deuteration of sulfoximines, for which the means of labelling are severely under met.Finally, our studies in the labelling of aryl sulfones led us to the serendipitous discovery of ether-directed HIE. This process was investigated with our novel NHC-P catalyst system, and a substrate scope established. Additionally, a potential application in form of labelling natural products, and natural product-like molecules has been proposed, with a series of three natural product-like molecules having been synthesised for attempts towards labelling
Scramjet combustion modeling using eddy dissipation model
Get PDFIn order to aid in the design of scramjet propulsion systems at high Mach number operation, this works considers the Eddy Dissipation Model (EDM) to describe the combustion process inside an open-access Computational Fluid Dynamics (CFD) solver. Typical CFD modeling approaches for turbulent supersonic reacting flows are associated with a high computational cost. This in turn inhibits the use of CFD in scramjet combustor design or in higher level preliminary designs such as the trajectory optimization process of a scramjet powered vehicle.;Instead, low-fidelity models are preferred to charaterize the propulsion system in the latter type of application. The EDM relies on simplified assumptions regarding the combustion process whose validity is thought to be prevalent at high Mach number scramjet operation. It is therefore a suitable candidate model in order to introduce more routinely CFD in scramjet preliminary design phases. As part of the present work, first steps include the selection of an open-source CFD solver followed by several validation studies.;After its implementation, a critical numerical analysis of the EDM is performed by considering three hydrogen-fueled experimental scramjet configurations with different fuel injection approaches. Its application is further investigated with a mainly kinetically controlled scramjet design where the underlying assumptions of the EDM are not valid anymore. Finally, the EDM is applied to a combustor design problem demonstrating the metrics of interest that can be relied on for this task.In order to aid in the design of scramjet propulsion systems at high Mach number operation, this works considers the Eddy Dissipation Model (EDM) to describe the combustion process inside an open-access Computational Fluid Dynamics (CFD) solver. Typical CFD modeling approaches for turbulent supersonic reacting flows are associated with a high computational cost. This in turn inhibits the use of CFD in scramjet combustor design or in higher level preliminary designs such as the trajectory optimization process of a scramjet powered vehicle.;Instead, low-fidelity models are preferred to charaterize the propulsion system in the latter type of application. The EDM relies on simplified assumptions regarding the combustion process whose validity is thought to be prevalent at high Mach number scramjet operation. It is therefore a suitable candidate model in order to introduce more routinely CFD in scramjet preliminary design phases. As part of the present work, first steps include the selection of an open-source CFD solver followed by several validation studies.;After its implementation, a critical numerical analysis of the EDM is performed by considering three hydrogen-fueled experimental scramjet configurations with different fuel injection approaches. Its application is further investigated with a mainly kinetically controlled scramjet design where the underlying assumptions of the EDM are not valid anymore. Finally, the EDM is applied to a combustor design problem demonstrating the metrics of interest that can be relied on for this task
The application of linear and nonlinear estimators of acoustic variability in the assessment of speech motor control in hypokinetic dysarthria
Get PDFTo improve diagnostic and outcome measures in the assessment and treatment of speech disorders, researchers and clinicians are always in search of new techniques to quantify speech impairment. This thesis investigates the relatively unexplored area of linear and nonlinear estimators of acoustic variability and their suitability for assessing the stability of movement patterns of speech organs. In particular, it focused on the estimators' ability to differentiate hypokinetic dysarthria from unimpaired speech, as well as speech of young adults from older adults. In addition, the variability results of hypokinetic dysarthric speakers were compared with the results of standard diagnostic assessments.;Twenty-three speakers with hypokinetic dysarthria and forty neurologically healthy individuals participated in the study. A series of sentence repetition tasks was devised with varying linguistic, cognitive and motor demands. A range of time-varying speech features was extracted from the acoustic signal in order to capture speech motor performance in a number of segmental and prosodic aspects of speech production.;The results showed that acoustic measures of variability were successful in classifying dysarthria and healthy speakers as well as adult speakers differing in age, and correlated with different clinical-based assessments.;The findings of this study indicate that the characterization of complex speech movements during phrase production when evaluating linguistic, cognitive, or motor demands within or between speaker groups cannot be reduced to a single task or speech property, but rather call for a multi-faceted approach in which distinct variability estimators, speech tasks and acoustic properties are evaluated simultaneously.To improve diagnostic and outcome measures in the assessment and treatment of speech disorders, researchers and clinicians are always in search of new techniques to quantify speech impairment. This thesis investigates the relatively unexplored area of linear and nonlinear estimators of acoustic variability and their suitability for assessing the stability of movement patterns of speech organs. In particular, it focused on the estimators' ability to differentiate hypokinetic dysarthria from unimpaired speech, as well as speech of young adults from older adults. In addition, the variability results of hypokinetic dysarthric speakers were compared with the results of standard diagnostic assessments.;Twenty-three speakers with hypokinetic dysarthria and forty neurologically healthy individuals participated in the study. A series of sentence repetition tasks was devised with varying linguistic, cognitive and motor demands. A range of time-varying speech features was extracted from the acoustic signal in order to capture speech motor performance in a number of segmental and prosodic aspects of speech production.;The results showed that acoustic measures of variability were successful in classifying dysarthria and healthy speakers as well as adult speakers differing in age, and correlated with different clinical-based assessments.;The findings of this study indicate that the characterization of complex speech movements during phrase production when evaluating linguistic, cognitive, or motor demands within or between speaker groups cannot be reduced to a single task or speech property, but rather call for a multi-faceted approach in which distinct variability estimators, speech tasks and acoustic properties are evaluated simultaneously
Adiabatic processes, noise, and stochastic algorithms for quantum computing and quantum simulation
Get PDFRapid developments in experiments provide promising platforms for realising quantum computation and quantum simulation. This, in turn, opens new possibilities for developing useful quantum algorithms and explaining complex many-body physics. The advantages of quantum computation have been demonstrated in a small range of subjects, but the potential applications of quantum algorithms for solving complex classical problems are still under investigation. Deeper understanding of complex many-body systems can lead to realising quantum simulation to study systems which are inaccessible by other means.This thesis studies different topics of quantum computation and quantum simulation.The first one is improving a quantum algorithm in adiabatic quantum computing, which can be used to solve classical problems like combinatorial optimisation problems and simulated annealing. We are able to reach a new bound of time cost for the algorithm which has a potential to achieve a speed up over standard adiabatic quantum computing. The second topic is to understand the amplitude noise in optical lattices in the context of adiabatic state preparation and the thermalisation of the energy introduced to the system. We identify regimes where introducing certain type of noise in experiments would improve the final fidelity of adiabatic state preparation, and demonstrate the robustness of the state preparation to imperfect noise implementations. We also discuss the competition between heating and dephasing effects, the energy introduced by non-adiabaticity and heating, and the thermalisation of the system after an application of amplitude noise on the lattice. The third topic is to design quantum algorithms to solve classical problems of fluid dynamics. We develop a quantum algorithm based around phase estimation that can be tailored to specific fluid dynamics problems and demonstrate a quantum speed up over classical Monte Carlo methods. This generates new bridge between quantum physics and fluid dynamics engineering, can be used to estimate the potential impact of quantum computers and provides feedback on requirements for implementing quantum algorithms on quantum devices.Rapid developments in experiments provide promising platforms for realising quantum computation and quantum simulation. This, in turn, opens new possibilities for developing useful quantum algorithms and explaining complex many-body physics. The advantages of quantum computation have been demonstrated in a small range of subjects, but the potential applications of quantum algorithms for solving complex classical problems are still under investigation. Deeper understanding of complex many-body systems can lead to realising quantum simulation to study systems which are inaccessible by other means.This thesis studies different topics of quantum computation and quantum simulation.The first one is improving a quantum algorithm in adiabatic quantum computing, which can be used to solve classical problems like combinatorial optimisation problems and simulated annealing. We are able to reach a new bound of time cost for the algorithm which has a potential to achieve a speed up over standard adiabatic quantum computing. The second topic is to understand the amplitude noise in optical lattices in the context of adiabatic state preparation and the thermalisation of the energy introduced to the system. We identify regimes where introducing certain type of noise in experiments would improve the final fidelity of adiabatic state preparation, and demonstrate the robustness of the state preparation to imperfect noise implementations. We also discuss the competition between heating and dephasing effects, the energy introduced by non-adiabaticity and heating, and the thermalisation of the system after an application of amplitude noise on the lattice. The third topic is to design quantum algorithms to solve classical problems of fluid dynamics. We develop a quantum algorithm based around phase estimation that can be tailored to specific fluid dynamics problems and demonstrate a quantum speed up over classical Monte Carlo methods. This generates new bridge between quantum physics and fluid dynamics engineering, can be used to estimate the potential impact of quantum computers and provides feedback on requirements for implementing quantum algorithms on quantum devices
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