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Development of a diagnostic device to predict clinically significant inflammation associated with cardiac surgery
No full textThis thesis was previously held under moratorium from 1st December 2016 until 4th June 2021.Background: Cardiopulmonary bypass deployment is known to cause an inflammatory response during open heart surgery. Inflammation involves the activation of different cascades such as coagulation, the complement system and cytokines. Although the immune system is the body's key defense mechanism against external assault, it can be injurious to the patient when the immune system is over-expressed, particularly in cohort of patients that experience a heightened and uncontrolled response. This exaggerated response results in autoimmune injury and may lead to poor post-operative outcomes, such as systemic inflammatory response syndrome and multi-organ failure. Aim of the work: This project was aimed to develop a predictive screening technology that enables clinicians to specify patients who may be at risk prior to open heart surgery. This project suggests a new approach to identifying these patients, through the development of a novel technology that will measure the extent of the inflammatory response following blood contact with extracorporeal systems. This work focuses on cardiopulmonary bypass, but the technology may also extend to other treatments and interventional modalities in which tissues, in particular blood, comes into contact with foreign surfaces.;Approach: A series of in-vitro studies on bovine blood were performed to investigate the role of two initiators of the inflammatory response (DEHP plasticised PVC and liquid DEHP itself) and the exaggeration of different pro-inflammatory cytokines levels. A clinical study was then undertaken in open heart surgery patients to confirm the preliminary outcomes from the in vitro studies and to specify the most appropriate plasma marker that predict patients at-risk of developing SIRS (focusing on IL-6,TNF-α and C-reactive protein). The clinical study was aimed to outline the most appropriate initiator and measuring technique for cytokine concentration (ELISA versus Fourier Transform Infrared Spectroscopy (FTIR)) and we sought to establish a final design configuration of the proposed screening technology. Results: The in vitro studies showed that both DEHP plasticised PVC and liquid DEHP are effective initiators of the inflammatory response. This was verified by the clinical investigations, and the data suggested that IL-6 with DEHP plasticised PVC is the most sensitive diagnostic marker that can identify patients prior to open heart surgery who are at risk of developing SIRS. Both analysing techniques (ELISA and FTIR) were shown to be suitable for the intended device development. However, FTIR - with its reduced complexity and processing time - was considered to be the best analytical modality for future ongoing development of the intended POC screening device. A basic prototype for this screening device (an activation chamber,separation and wicking membrane and device schematics) was developed and future work is necessary to deliver the device to the clinic.Background: Cardiopulmonary bypass deployment is known to cause an inflammatory response during open heart surgery. Inflammation involves the activation of different cascades such as coagulation, the complement system and cytokines. Although the immune system is the body's key defense mechanism against external assault, it can be injurious to the patient when the immune system is over-expressed, particularly in cohort of patients that experience a heightened and uncontrolled response. This exaggerated response results in autoimmune injury and may lead to poor post-operative outcomes, such as systemic inflammatory response syndrome and multi-organ failure. Aim of the work: This project was aimed to develop a predictive screening technology that enables clinicians to specify patients who may be at risk prior to open heart surgery. This project suggests a new approach to identifying these patients, through the development of a novel technology that will measure the extent of the inflammatory response following blood contact with extracorporeal systems. This work focuses on cardiopulmonary bypass, but the technology may also extend to other treatments and interventional modalities in which tissues, in particular blood, comes into contact with foreign surfaces.;Approach: A series of in-vitro studies on bovine blood were performed to investigate the role of two initiators of the inflammatory response (DEHP plasticised PVC and liquid DEHP itself) and the exaggeration of different pro-inflammatory cytokines levels. A clinical study was then undertaken in open heart surgery patients to confirm the preliminary outcomes from the in vitro studies and to specify the most appropriate plasma marker that predict patients at-risk of developing SIRS (focusing on IL-6,TNF-α and C-reactive protein). The clinical study was aimed to outline the most appropriate initiator and measuring technique for cytokine concentration (ELISA versus Fourier Transform Infrared Spectroscopy (FTIR)) and we sought to establish a final design configuration of the proposed screening technology. Results: The in vitro studies showed that both DEHP plasticised PVC and liquid DEHP are effective initiators of the inflammatory response. This was verified by the clinical investigations, and the data suggested that IL-6 with DEHP plasticised PVC is the most sensitive diagnostic marker that can identify patients prior to open heart surgery who are at risk of developing SIRS. Both analysing techniques (ELISA and FTIR) were shown to be suitable for the intended device development. However, FTIR - with its reduced complexity and processing time - was considered to be the best analytical modality for future ongoing development of the intended POC screening device. A basic prototype for this screening device (an activation chamber,separation and wicking membrane and device schematics) was developed and future work is necessary to deliver the device to the clinic
Dictionary learning for scalable sparse image representation
Get PDFModern era of signal processing has developed many technical tools for recording and processing large and growing amount of data together with algorithms specialised for data analysis. This gives rise to new challenges in terms of data processing and modelling data representation. Fields ranging from experimental sciences, astronomy, computer vision,neuroscience mobile networks etc., are all in constant search for scalable and efficient data processing tools which would enable more effective analysis of continuous video streams containing millions of pixels. Therefore, the question of digital signal representation is still of high importance, despite the fact that it has been the topic of a significant amount of work in the past. Moreover, developing new data processing methods also affects the quality of everyday life, where devices such as CCD sensors from digital cameras or cell phones are intensively used for entertainment purposes. Specifically, one of the novel processing tools is signal sparse coding which represents signals as linear combinations of a few representational basis vectors i.e., atoms given an overcomplete dictionary. Applications that employ sparse representation are many such as denoising, compression, and regularisation in inverse problems, feature extraction, and more. In this thesis we introduce and study a particular signal representation denoted as the scalable sparse coding. It is based on a novel design for the dictionary learning algorithm, which has proven to be effective for scalable sparse representation of many modalities such as high motion video sequences, natural and solar images. The proposed algorithm is built upon the foundation of the K-SVD framework originally designed to learn non-scalable dictionaries for natural images. The scalable dictionary learning design is mainly motivated by the main perception characteristics of the Human Visual System (HVS) mechanism. Specifically, its core structure relies on the exploitation of the spatial high-frequency image components and contrast variations in order to achieve visual scene objects identification at all scalable levels. The implementation of HVS properties is carried out by introducing a semi-random Morphological Component Analysis (MCA) based initialisation of the scalable dictionary and the regularisation of its atom's update mechanism. Subsequently, this enables scalable sparse image reconstruction. In general, dictionary learning for sparse representations leads to state-of-the-art image restoration results for several different problems in the field of image processing. Experiments in this thesis show that these are equally achievable by accommodating all dictionary elements to tailor the scalable data representation and reconstruction, hence modelling data that admit sparse representation in a novel manner. Furthermore, achieved results demonstrateand validate the practicality of the proposed scheme making it a promising candidate for many practical applications involving both time scalable display, denoising and scalable compressive sensing (CS). Performed simulations include scalable sparse recovery for representation of static and dynamic data changing over time such as video sequences and natural images. Lastly, we contribute novel approaches for scalable denoising and contrast enhancement (CE), applied on solar images corrupted with pixel-dependent Poisson and zero-mean additive white Gaussian noise. Given that solar data contain noise introduced by charge-coupled devices within the on-board acquisition system these artefacts, prior to image analysis, have to be removed. Thus, novel image denoising and contrast enhancement methods are necessary for solar preprocessing.Modern era of signal processing has developed many technical tools for recording and processing large and growing amount of data together with algorithms specialised for data analysis. This gives rise to new challenges in terms of data processing and modelling data representation. Fields ranging from experimental sciences, astronomy, computer vision,neuroscience mobile networks etc., are all in constant search for scalable and efficient data processing tools which would enable more effective analysis of continuous video streams containing millions of pixels. Therefore, the question of digital signal representation is still of high importance, despite the fact that it has been the topic of a significant amount of work in the past. Moreover, developing new data processing methods also affects the quality of everyday life, where devices such as CCD sensors from digital cameras or cell phones are intensively used for entertainment purposes. Specifically, one of the novel processing tools is signal sparse coding which represents signals as linear combinations of a few representational basis vectors i.e., atoms given an overcomplete dictionary. Applications that employ sparse representation are many such as denoising, compression, and regularisation in inverse problems, feature extraction, and more. In this thesis we introduce and study a particular signal representation denoted as the scalable sparse coding. It is based on a novel design for the dictionary learning algorithm, which has proven to be effective for scalable sparse representation of many modalities such as high motion video sequences, natural and solar images. The proposed algorithm is built upon the foundation of the K-SVD framework originally designed to learn non-scalable dictionaries for natural images. The scalable dictionary learning design is mainly motivated by the main perception characteristics of the Human Visual System (HVS) mechanism. Specifically, its core structure relies on the exploitation of the spatial high-frequency image components and contrast variations in order to achieve visual scene objects identification at all scalable levels. The implementation of HVS properties is carried out by introducing a semi-random Morphological Component Analysis (MCA) based initialisation of the scalable dictionary and the regularisation of its atom's update mechanism. Subsequently, this enables scalable sparse image reconstruction. In general, dictionary learning for sparse representations leads to state-of-the-art image restoration results for several different problems in the field of image processing. Experiments in this thesis show that these are equally achievable by accommodating all dictionary elements to tailor the scalable data representation and reconstruction, hence modelling data that admit sparse representation in a novel manner. Furthermore, achieved results demonstrateand validate the practicality of the proposed scheme making it a promising candidate for many practical applications involving both time scalable display, denoising and scalable compressive sensing (CS). Performed simulations include scalable sparse recovery for representation of static and dynamic data changing over time such as video sequences and natural images. Lastly, we contribute novel approaches for scalable denoising and contrast enhancement (CE), applied on solar images corrupted with pixel-dependent Poisson and zero-mean additive white Gaussian noise. Given that solar data contain noise introduced by charge-coupled devices within the on-board acquisition system these artefacts, prior to image analysis, have to be removed. Thus, novel image denoising and contrast enhancement methods are necessary for solar preprocessing
Essays in the multi-sectoral economic modelling of energy technologies and policies
Get PDFPhD by publication.Energy policy goals across many countries and regions seek to achieve multiple goals simultaneously, including to reduce emissions, improve energy security and enhance energy affordability. A further goal is that energy policy should make a positive contribution to economic development of the area, or that (at least) energy policy changes should not worsen economic outcomes. It is the contention of this thesis is that ex ante multi-sectoral economic modelling approaches - specifically, Input-Output (IO), Social Accounting Matrix (SAM) and Computable General Equilibrium (CGE) analysis - can usefully explore the potential economic and environmental consequences of energy technologies and policies. Specifically, these models can assist in identifying and quantifying the impact of policies on the competing goals of energy policy, and so improve the design of appropriate energy policy. The thesis consists of six papers which apply multi-sectoral modelling approaches, all of which were published in peer-reviewed academic journals between 2007 and 2015 (inclusive). Each paper describes and/or extends multi-sectoral empirical economic analysis and modelling. The applications range from specific energy technologies - an onshore windfarm development, biofuels and developments in marine renewable energy technology - to potential energy policies - a (revenue-neutral) carbon tax and improvements in the efficiency of energy in production. This thesis explores the fundamental characteristics, assumptions and uses of "fixed" and "flex-" price models. Working sequentially from IO and SAM to CGE methods, it explores the particular strengths, weaknesses and usefulness of each of these modelling approaches, and explains the contribution of the papers included in this PhD by published works to the academic literature and pertinent policy issues.Energy policy goals across many countries and regions seek to achieve multiple goals simultaneously, including to reduce emissions, improve energy security and enhance energy affordability. A further goal is that energy policy should make a positive contribution to economic development of the area, or that (at least) energy policy changes should not worsen economic outcomes. It is the contention of this thesis is that ex ante multi-sectoral economic modelling approaches - specifically, Input-Output (IO), Social Accounting Matrix (SAM) and Computable General Equilibrium (CGE) analysis - can usefully explore the potential economic and environmental consequences of energy technologies and policies. Specifically, these models can assist in identifying and quantifying the impact of policies on the competing goals of energy policy, and so improve the design of appropriate energy policy. The thesis consists of six papers which apply multi-sectoral modelling approaches, all of which were published in peer-reviewed academic journals between 2007 and 2015 (inclusive). Each paper describes and/or extends multi-sectoral empirical economic analysis and modelling. The applications range from specific energy technologies - an onshore windfarm development, biofuels and developments in marine renewable energy technology - to potential energy policies - a (revenue-neutral) carbon tax and improvements in the efficiency of energy in production. This thesis explores the fundamental characteristics, assumptions and uses of "fixed" and "flex-" price models. Working sequentially from IO and SAM to CGE methods, it explores the particular strengths, weaknesses and usefulness of each of these modelling approaches, and explains the contribution of the papers included in this PhD by published works to the academic literature and pertinent policy issues
Detection of chronic wound infection using impedance spectroscopy
No full textChronic wounds are a rapidly growing burden to patients and healthcare systems globally. The rising incidence of both obesity and diabetes worldwide, coupled with an aging population, are contributors to predictions that a greater number of patients will exhibit chronic wounds in the future. It has been shown that bacteria in wounds form persistent biofilms. Successful wound management calls for rapid, accurate diagnosis to control infections, as well as minimizing disruption to the wound site. Historically, clinical identification of infection at a wound site has relied on swabbing and culturing methods, and in recent years progress has been made in using electrochemical biosensors for the rapid detection of microorganisms. This study explores the detection of infections using impedance spectroscopy to monitor bacteria.Initial electrochemical impedance spectroscopy experiments using label-less carbon screen printed electrodes were conducted to characterise the impedance signatures of Staphylococcus aureus, Pseudomonas aeruginosa, and Enterococcus faecalis. These bacteria, which are commonly found in chronic wound infections, were cultured in both rich laboratory media and simulated wound fluid. In the final part of the study a wound bed model was produced that simulated the environment representative of a wound infection including two dressing types, one honey-based and one silicone. Experiments were performed to assess the effectiveness of the impedance detection technique for chronic wound infections using this model.Differences in impedance characteristics were seen across bacterial strains in laboratory media and simulated wound fluid. The greatest changes were seen in P. aeruginosa, with smaller impedance signatures identified for S. aurues. Signatures were also observed for E. faecalis with significant differences seen in some regions of the impedance spectrum. Additionally, it was found that a honey-based dressing resulted in lower cell density of P. aeruginosa colonies after 72 hours and that prominent features in the phase component of impedance were present. Findings from this study support the possibility that impedance spectroscopy could be used for the identification of chronic wound bacteria in a future point of care device.Chronic wounds are a rapidly growing burden to patients and healthcare systems globally. The rising incidence of both obesity and diabetes worldwide, coupled with an aging population, are contributors to predictions that a greater number of patients will exhibit chronic wounds in the future. It has been shown that bacteria in wounds form persistent biofilms. Successful wound management calls for rapid, accurate diagnosis to control infections, as well as minimizing disruption to the wound site. Historically, clinical identification of infection at a wound site has relied on swabbing and culturing methods, and in recent years progress has been made in using electrochemical biosensors for the rapid detection of microorganisms. This study explores the detection of infections using impedance spectroscopy to monitor bacteria.Initial electrochemical impedance spectroscopy experiments using label-less carbon screen printed electrodes were conducted to characterise the impedance signatures of Staphylococcus aureus, Pseudomonas aeruginosa, and Enterococcus faecalis. These bacteria, which are commonly found in chronic wound infections, were cultured in both rich laboratory media and simulated wound fluid. In the final part of the study a wound bed model was produced that simulated the environment representative of a wound infection including two dressing types, one honey-based and one silicone. Experiments were performed to assess the effectiveness of the impedance detection technique for chronic wound infections using this model.Differences in impedance characteristics were seen across bacterial strains in laboratory media and simulated wound fluid. The greatest changes were seen in P. aeruginosa, with smaller impedance signatures identified for S. aurues. Signatures were also observed for E. faecalis with significant differences seen in some regions of the impedance spectrum. Additionally, it was found that a honey-based dressing resulted in lower cell density of P. aeruginosa colonies after 72 hours and that prominent features in the phase component of impedance were present. Findings from this study support the possibility that impedance spectroscopy could be used for the identification of chronic wound bacteria in a future point of care device
Uncertain futures : exploring the economic consequences of school-leaver trajectories in Scotland - methodological challenges, policy implications, and future research
No full textDisadvantage in early life is often linked to disadvantage later in life. This can be in terms of school performance and ultimately employment status. Inequality is prevalent in Scotland, especially amongst young people - this can affect the pathways, or trajectories, they then take through life. Downstream interventions have been implemented to tackle such issues but the evidence of their success, in terms of outcomes for young people, is fragmented. Carrying out research to determine such outcomes is often infeasible or unethical.This research first learns from studies aiming to estimate the costs of life trajectories of young people. Complexity in implementing costing methodologies to socially embedded contexts comes in terms of the lack of common costing framework, the uncertainty over which consequences to attribute to the problem, the exact cost to attach to each consequence, and when the cost is to be incurred across the life-course.Using direct costs to the Scottish Government, this research applies costs to eight trajectories school-leavers might take based on school-leaver destinations (Higher Education, Further Education, and 'leaving education') with the final outcome states being employment status. The costliest trajectories are those involving extended periods of time in unemployment. Further analysis through a decision tree model and some basic employment rates post-HE/FE/school, finds, given the assumptions made, that it will always seem favourable to leave education. It is concluded that this is because the cost of unemployment is significantly underestimated here, and the lack of consideration of the higher return on investment which HE/FE should allow in terms of tax revenues. These aspects are considered through a proposal of future research.The first phase of the proposed research involves the use of systems mapping techniques to better understand the systemic issues of how young people get trapped in cycles of disadvantage and the levers to alleviate them of such cycles; the second phase continues the quantitative modelling of this research to develop a more realistic picture of trajectory costs and where cost savings might be made; and the third phase proposes the application of expert judgement elicitation to use experts to consider the potential effectiveness of different intervention models where the evidence of such models is lacking.Disadvantage in early life is often linked to disadvantage later in life. This can be in terms of school performance and ultimately employment status. Inequality is prevalent in Scotland, especially amongst young people - this can affect the pathways, or trajectories, they then take through life. Downstream interventions have been implemented to tackle such issues but the evidence of their success, in terms of outcomes for young people, is fragmented. Carrying out research to determine such outcomes is often infeasible or unethical.This research first learns from studies aiming to estimate the costs of life trajectories of young people. Complexity in implementing costing methodologies to socially embedded contexts comes in terms of the lack of common costing framework, the uncertainty over which consequences to attribute to the problem, the exact cost to attach to each consequence, and when the cost is to be incurred across the life-course.Using direct costs to the Scottish Government, this research applies costs to eight trajectories school-leavers might take based on school-leaver destinations (Higher Education, Further Education, and 'leaving education') with the final outcome states being employment status. The costliest trajectories are those involving extended periods of time in unemployment. Further analysis through a decision tree model and some basic employment rates post-HE/FE/school, finds, given the assumptions made, that it will always seem favourable to leave education. It is concluded that this is because the cost of unemployment is significantly underestimated here, and the lack of consideration of the higher return on investment which HE/FE should allow in terms of tax revenues. These aspects are considered through a proposal of future research.The first phase of the proposed research involves the use of systems mapping techniques to better understand the systemic issues of how young people get trapped in cycles of disadvantage and the levers to alleviate them of such cycles; the second phase continues the quantitative modelling of this research to develop a more realistic picture of trajectory costs and where cost savings might be made; and the third phase proposes the application of expert judgement elicitation to use experts to consider the potential effectiveness of different intervention models where the evidence of such models is lacking
FEL theory in the ION channel wiggler
Get PDFThe ion channel laser (ICL) is an ultra-compact version of the free-electron laser (FEL),with the wiggler replaced by an ion channel. Given its small size and the large wiggler field that can be created within a small volume, it has enormous potential for generating high-frequency coherent radiation. Previous studies of the ICL [1,5], however, have assumed transverse momentum amplitudes that are unrealistically small for experiments, and thus concluded that high-gain high-frequency coherent radiation generation using the ICL is infeasible.In contrast, this thesis shows that this restriction can be removed by correctly taking into account the dependence of the resonance between oscillations and emitted field on the betatron amplitude, which must be treated as variable. The ICL model with this essential addition is described using the well-known formalism for the FEL [3]. Both steady-state and spatio-temporal analyses of the resulting scaled equations show a realistic prospect of building a compact ICL source for fundamental wavelengths down to the UV, with harmonics potentially extending to X-rays. The gain parameter ρ can attain values of the order of 0.01-0.1, which permits driving an ICL with electron bunches with realistic emittance and achieving a radiation power gain comparable to FEL over a small distance.In addition, we present the first results of superradiant simulations for the ICL, also within the framework of the scaled formalism for the FEL, taking into account propagation effects, as well as a full SASE simulation using shot noise as the startup.The ion channel laser (ICL) is an ultra-compact version of the free-electron laser (FEL),with the wiggler replaced by an ion channel. Given its small size and the large wiggler field that can be created within a small volume, it has enormous potential for generating high-frequency coherent radiation. Previous studies of the ICL [1,5], however, have assumed transverse momentum amplitudes that are unrealistically small for experiments, and thus concluded that high-gain high-frequency coherent radiation generation using the ICL is infeasible.In contrast, this thesis shows that this restriction can be removed by correctly taking into account the dependence of the resonance between oscillations and emitted field on the betatron amplitude, which must be treated as variable. The ICL model with this essential addition is described using the well-known formalism for the FEL [3]. Both steady-state and spatio-temporal analyses of the resulting scaled equations show a realistic prospect of building a compact ICL source for fundamental wavelengths down to the UV, with harmonics potentially extending to X-rays. The gain parameter ρ can attain values of the order of 0.01-0.1, which permits driving an ICL with electron bunches with realistic emittance and achieving a radiation power gain comparable to FEL over a small distance.In addition, we present the first results of superradiant simulations for the ICL, also within the framework of the scaled formalism for the FEL, taking into account propagation effects, as well as a full SASE simulation using shot noise as the startup
Regulatory framework for adjudicators in the Malaysian construction industry
Get PDFStrathclyde theses - ask staff. Thesis no. : T14377Following the precedent move by the United Kingdom when it enacted the Housing, Grants, Construction and Regeneration Act 1996 (HGCRA 1996) in 1998, the enactment of the Construction Industry Payment and Adjudication Act 2012 (CIPA 2012) in 2014 is expected to improve the cash flow problems in the construction industry in Malaysia. Parallel with statutory needs to resolve disputes via adjudication, the statutory adjudicator exists to conduct the adjudication process. However, in contrast with the Building and Construction Industry Security of Payment Act 2004 (SOPA 2004) in Singapore, HGCRA 1996 and CIPA 2012 does not provide a mandatory regulatory framework for adjudicators. In view of that issue, the author aims to identify and test an appropriate regulatory framework for adjudicators in Malaysia by comparing and contrasting the existing regulatory framework in the UK, Singapore, New Zealand and Malaysia. In addition, the author will also explore the current regulatory framework for construction professionals and legal practitioners since both professions made up more than 90% of adjudicators in the UK, Singapore, New Zealand and Malaysia.Towards the journey to achieve the aim of the research, the author will start by exploring the relevant underlying theories of existing regulatory framework for construction professionals, legal practitioners and adjudicators in the UK, New Zealand, Singapore and Malaysia. The author will also address and articulate the theory behind the existence of adjudicators and the fundamental theory on relevant skill and knowledge for adjudicators. These findings will help to support the process of developing theoretical regulatory framework that will be used as a guide to identify an appropriate and credible regulatory framework for adjudicators in Malaysia. With the theoretical regulatory framework in hand, the author has sought to test empirically the framework practicality within the Malaysian context via a small scale of evaluative studies. The evaluative studies proven to be a big step to understand the acceptance of the advocated theoretical regulatory framework for adjudicators. Ultimately, it can be concluded that the propose regulatory framework for adjudicators in Malaysia is tested and approved via the small scale studies.Following the precedent move by the United Kingdom when it enacted the Housing, Grants, Construction and Regeneration Act 1996 (HGCRA 1996) in 1998, the enactment of the Construction Industry Payment and Adjudication Act 2012 (CIPA 2012) in 2014 is expected to improve the cash flow problems in the construction industry in Malaysia. Parallel with statutory needs to resolve disputes via adjudication, the statutory adjudicator exists to conduct the adjudication process. However, in contrast with the Building and Construction Industry Security of Payment Act 2004 (SOPA 2004) in Singapore, HGCRA 1996 and CIPA 2012 does not provide a mandatory regulatory framework for adjudicators. In view of that issue, the author aims to identify and test an appropriate regulatory framework for adjudicators in Malaysia by comparing and contrasting the existing regulatory framework in the UK, Singapore, New Zealand and Malaysia. In addition, the author will also explore the current regulatory framework for construction professionals and legal practitioners since both professions made up more than 90% of adjudicators in the UK, Singapore, New Zealand and Malaysia.Towards the journey to achieve the aim of the research, the author will start by exploring the relevant underlying theories of existing regulatory framework for construction professionals, legal practitioners and adjudicators in the UK, New Zealand, Singapore and Malaysia. The author will also address and articulate the theory behind the existence of adjudicators and the fundamental theory on relevant skill and knowledge for adjudicators. These findings will help to support the process of developing theoretical regulatory framework that will be used as a guide to identify an appropriate and credible regulatory framework for adjudicators in Malaysia. With the theoretical regulatory framework in hand, the author has sought to test empirically the framework practicality within the Malaysian context via a small scale of evaluative studies. The evaluative studies proven to be a big step to understand the acceptance of the advocated theoretical regulatory framework for adjudicators. Ultimately, it can be concluded that the propose regulatory framework for adjudicators in Malaysia is tested and approved via the small scale studies
A synthetic biology approach to the biosynthesis of novel pyrrole-amide antibiotics
Get PDFNovel antibiotics are desperately needed. We are on the verge of the pre-antibiotic era, with bacteria resistant to last resort drugs spreading quickly worldwide. Natural products, or chemical molecules produced by living organisms, evolved over time to interact with biological targets following rules that researchers have not yet outlined fully. However microorganisms, once the source of most of the drugs we use today, were abandoned in favor of synthetic chemistry, under the false premise that natural sources were depleted.;When pursuing novel antimicrobials, two options are in hand, either drug discovery or drug functionalisation. In this thesis, approaches that were left on the golden era of antibiotic discovery due to technological limitations are revisited to produce derivatives of congocidine and distamycin. These two natural products are pyrrole-amide peptide antibiotics, characterised by antibiotic, antifungal, antiviral and antitumoral properties, which arise from their non-covalent DNA-binding properties.;Since both antibiotics are chemically very close, this thesis explores the combinatorial biosynthetic opportunities to exploit between the pathways that encodes them. Their chemical outline enables them to bind rich AT sequences in the minor groove of the DNA, with different preferred motifs according to specific differences in peptide length and functional groups. Research on synthetic compounds imitating these two natural products, have shown that the DNA binding affinity can be modulated by peptide length and heterocycle content.;As synthetic chemistry represents an inefficient approach for the production of these derivatised compounds based on the natural scaffold of concocidine, the in-vivo substitution of the pyrrole rings for other heterocycles such as imidazole or thiazole is pursued through a mutasynthetic approach. The last part of this study focuses on the resistance mechanism present in both clusters. Since both antibiotics are closely related, the study of their resistance mechanism can help understand how natural antimicrobial evolution shapes natural antibiotic resistance, and the structure to activity relationship of novel compounds are explored.Novel antibiotics are desperately needed. We are on the verge of the pre-antibiotic era, with bacteria resistant to last resort drugs spreading quickly worldwide. Natural products, or chemical molecules produced by living organisms, evolved over time to interact with biological targets following rules that researchers have not yet outlined fully. However microorganisms, once the source of most of the drugs we use today, were abandoned in favor of synthetic chemistry, under the false premise that natural sources were depleted.;When pursuing novel antimicrobials, two options are in hand, either drug discovery or drug functionalisation. In this thesis, approaches that were left on the golden era of antibiotic discovery due to technological limitations are revisited to produce derivatives of congocidine and distamycin. These two natural products are pyrrole-amide peptide antibiotics, characterised by antibiotic, antifungal, antiviral and antitumoral properties, which arise from their non-covalent DNA-binding properties.;Since both antibiotics are chemically very close, this thesis explores the combinatorial biosynthetic opportunities to exploit between the pathways that encodes them. Their chemical outline enables them to bind rich AT sequences in the minor groove of the DNA, with different preferred motifs according to specific differences in peptide length and functional groups. Research on synthetic compounds imitating these two natural products, have shown that the DNA binding affinity can be modulated by peptide length and heterocycle content.;As synthetic chemistry represents an inefficient approach for the production of these derivatised compounds based on the natural scaffold of concocidine, the in-vivo substitution of the pyrrole rings for other heterocycles such as imidazole or thiazole is pursued through a mutasynthetic approach. The last part of this study focuses on the resistance mechanism present in both clusters. Since both antibiotics are closely related, the study of their resistance mechanism can help understand how natural antimicrobial evolution shapes natural antibiotic resistance, and the structure to activity relationship of novel compounds are explored
Neuropsychological functions and pedestrian behaviour in children with and without ADHD
Get PDFThis thesis examines the development of pedestrian skill level and the extent to which cognitive functioning underpins this amongst children with and without Attention Deficit Hyperactivity Disorder (ADHD). Three studies are reported, the first of which is an examination of the development of three pedestrian skills (safe place finding, visual gap timing and predicting road user intentions) and four aspects of cognitive function amongst typically developing children aged 5 to 12 years. Results from the first study revealed clear age related improvement in both pedestrian skill level and cognitive function. Inhibitory control, spatial working memory as well as non-executive delayed short term memory (but not risk taking) predicted children's pedestrian skill level. The second study examined developmental differences in pedestrian skill level and cognitive function by comparing the abilities of medication naive children with ADHD and matched controls aged 5-12 years on the same three tasks assessing pedestrian skill level and three aspects of cognitive function. Findings from the second study revealed significant between group differences in both cognitive function and pedestrian skill level such that children with ADHD performed markedly less well than controls. Whilst inhibitory control, spatial working memory and delayed short term memory predicted pedestrian skill level for control children, these relationships were for the most part, absent amongst children with ADHD. The final study was a longitudinal follow up study of a subset of the children with and without ADHD who took part in study 2. In study 3 the same tasks were administered to children at a mean time of 14 months following their participation in study 2, by which point all of the children with ADHD were being treated with stimulant medication. The findings of study 3 revealed medication had normalised the performance of children with ADHD on tasks assessing inhibitory control and non-executive delayed short term memory but had no impact on spatial working memory. Medication had also normalised performance on two of the three tasks assessing pedestrian skill level and improved most measures of performance on a third. These results have implications for clinicians and educators working with children with ADHD and highlight scope for future research to develop and trial interventions which take account of the relationship between cognitive function and pedestrian skill level amongst both typically developing children and the more vulnerable group of children with ADHD.This thesis examines the development of pedestrian skill level and the extent to which cognitive functioning underpins this amongst children with and without Attention Deficit Hyperactivity Disorder (ADHD). Three studies are reported, the first of which is an examination of the development of three pedestrian skills (safe place finding, visual gap timing and predicting road user intentions) and four aspects of cognitive function amongst typically developing children aged 5 to 12 years. Results from the first study revealed clear age related improvement in both pedestrian skill level and cognitive function. Inhibitory control, spatial working memory as well as non-executive delayed short term memory (but not risk taking) predicted children's pedestrian skill level. The second study examined developmental differences in pedestrian skill level and cognitive function by comparing the abilities of medication naive children with ADHD and matched controls aged 5-12 years on the same three tasks assessing pedestrian skill level and three aspects of cognitive function. Findings from the second study revealed significant between group differences in both cognitive function and pedestrian skill level such that children with ADHD performed markedly less well than controls. Whilst inhibitory control, spatial working memory and delayed short term memory predicted pedestrian skill level for control children, these relationships were for the most part, absent amongst children with ADHD. The final study was a longitudinal follow up study of a subset of the children with and without ADHD who took part in study 2. In study 3 the same tasks were administered to children at a mean time of 14 months following their participation in study 2, by which point all of the children with ADHD were being treated with stimulant medication. The findings of study 3 revealed medication had normalised the performance of children with ADHD on tasks assessing inhibitory control and non-executive delayed short term memory but had no impact on spatial working memory. Medication had also normalised performance on two of the three tasks assessing pedestrian skill level and improved most measures of performance on a third. These results have implications for clinicians and educators working with children with ADHD and highlight scope for future research to develop and trial interventions which take account of the relationship between cognitive function and pedestrian skill level amongst both typically developing children and the more vulnerable group of children with ADHD
The development of analytical approaches to profile Scotch Whisky colour
Get PDFAttenuated total reflectance mid-infrared (ATR-MIR) spectrometry and liquid chromatography - mass spectrometry (LC-MS) have been investigated as techniques for profiling Scotch Whisky colour (naturally derived and that originating from E150a caramel). ATR-MIR was initially implemented to investigate caramel colourants and it was found that profiles dominated by colour constituents could be obtained by analysing dried residues of caramel solutions. Using this approach, it was possible to differentiate between legally permitted E150a caramels and the three other EU recognised classes (not permitted in Scotch). It was also possible to obtain unique profiles for different E150a formulations. These distinctions between caramels were maintained when dissolved in a typical blend whisky, a finding that could provide the opportunity to use E150a caramels as inherent authenticity markers in Scotch. Additional factors such as changing caramel concentration, varying the blend matrix, and caramel fade were also investigated in this work and found in some cases to influence spectra.Work progressed from the above findings to compare multivariate data analysis tools for the prediction of caramel identities, based on their characteristic spectra. PCA with GLSW and PC-DFA were found to be most successful but would require background whisky matrices to be accounted for during calibration. Analysis of LC-MS data complemented that of ATR-MIR, showing the potential to distinguish between caramel materials as described above. The advantage of ATR-MIR over LC-MS is its adaptability for field studies as a portable device, LC-MS on the other hand has the ability to identify components responsible for sample distinctions and it was possible in this work to find components characteristic of different caramels. Advanced software also enabled tentative structures to be assigned to some components. Additional studies using LC-MS highlighted its potential for other applications relating to Scotch, for example components characteristic of different cask histories and maturation ages were found.Attenuated total reflectance mid-infrared (ATR-MIR) spectrometry and liquid chromatography - mass spectrometry (LC-MS) have been investigated as techniques for profiling Scotch Whisky colour (naturally derived and that originating from E150a caramel). ATR-MIR was initially implemented to investigate caramel colourants and it was found that profiles dominated by colour constituents could be obtained by analysing dried residues of caramel solutions. Using this approach, it was possible to differentiate between legally permitted E150a caramels and the three other EU recognised classes (not permitted in Scotch). It was also possible to obtain unique profiles for different E150a formulations. These distinctions between caramels were maintained when dissolved in a typical blend whisky, a finding that could provide the opportunity to use E150a caramels as inherent authenticity markers in Scotch. Additional factors such as changing caramel concentration, varying the blend matrix, and caramel fade were also investigated in this work and found in some cases to influence spectra.Work progressed from the above findings to compare multivariate data analysis tools for the prediction of caramel identities, based on their characteristic spectra. PCA with GLSW and PC-DFA were found to be most successful but would require background whisky matrices to be accounted for during calibration. Analysis of LC-MS data complemented that of ATR-MIR, showing the potential to distinguish between caramel materials as described above. The advantage of ATR-MIR over LC-MS is its adaptability for field studies as a portable device, LC-MS on the other hand has the ability to identify components responsible for sample distinctions and it was possible in this work to find components characteristic of different caramels. Advanced software also enabled tentative structures to be assigned to some components. Additional studies using LC-MS highlighted its potential for other applications relating to Scotch, for example components characteristic of different cask histories and maturation ages were found
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