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Renewable energy injustices : promoting an African communitarian approach to global energy justice through international law
No full textFunctionalizing silk hydrogels with nanoparticles and fibres
Full text linkThis research explores the development of composite silk hydrogels by incorporating different types of silk nanoparticles and microfibres, including Antheraea mylitta (Tasar) silk. The aim was to generate hydrogel composites to ultimately modulate the mechanical properties of Bombyx mori (B. mori) silk hydrogels and enhance cell attachment. B. mori silk lacks the arginine-glycine-aspartic acid (RGD) sequence that is used for cell adhesion. Therefore, introducing RGD-containing Tasar silk within B. mori hydrogels is particularly interesting. This thesis investigated the mechanical properties of silk hydrogels containing various nanoparticles including silica nanoparticles (Chapter 2 and Chapter 3), B. mori and Tasar silk nanoparticles (Chapter 3) as well as silk microfibres . These hydrogel composites were subjected to cell adhesion studies, using DU-145 cells and induced pluripotent stem cell-derived MSCs (iPSCs-MSCs). The research found that ilk hydrogels loaded with 5% w/v silica nanoparticles exhibited higher stiffness than those with lower concentrations (Chapter 2). In Chapter 3, the results showed that silk hydrogels functionalised with nanoparticles had similar stiffness but with variations in stress relaxation while maintaining consistent cell attachment. Silk hydrogels inforced with B. mori and Tasar silk fibres enhanced short-term cell proliferation and attachment, with Tasar silk microfibres being particularly effective. However, cell attachment on silk hydrogels was still less than on tissue culture plastic. Overall, this thesis generated composite silk hydrogels using a spectrum of nanoparticles and silk fibres that in turn modulated the mechanical properties and especially those hydrogels reinforced with silk microfibres, promote short-term cell growth and adhesion.This research explores the development of composite silk hydrogels by incorporating different types of silk nanoparticles and microfibres, including Antheraea mylitta (Tasar) silk. The aim was to generate hydrogel composites to ultimately modulate the mechanical properties of Bombyx mori (B. mori) silk hydrogels and enhance cell attachment. B. mori silk lacks the arginine-glycine-aspartic acid (RGD) sequence that is used for cell adhesion. Therefore, introducing RGD-containing Tasar silk within B. mori hydrogels is particularly interesting. This thesis investigated the mechanical properties of silk hydrogels containing various nanoparticles including silica nanoparticles (Chapter 2 and Chapter 3), B. mori and Tasar silk nanoparticles (Chapter 3) as well as silk microfibres . These hydrogel composites were subjected to cell adhesion studies, using DU-145 cells and induced pluripotent stem cell-derived MSCs (iPSCs-MSCs). The research found that ilk hydrogels loaded with 5% w/v silica nanoparticles exhibited higher stiffness than those with lower concentrations (Chapter 2). In Chapter 3, the results showed that silk hydrogels functionalised with nanoparticles had similar stiffness but with variations in stress relaxation while maintaining consistent cell attachment. Silk hydrogels inforced with B. mori and Tasar silk fibres enhanced short-term cell proliferation and attachment, with Tasar silk microfibres being particularly effective. However, cell attachment on silk hydrogels was still less than on tissue culture plastic. Overall, this thesis generated composite silk hydrogels using a spectrum of nanoparticles and silk fibres that in turn modulated the mechanical properties and especially those hydrogels reinforced with silk microfibres, promote short-term cell growth and adhesion
Neuromorphic nanophotonic systems for artificial intelligence
Full text linkOver the last decade, we have witnessed an astonishing pace of development in the field of artificial intelligence (AI), followed by proliferation of AI algorithms into virtually every domain of our society. While modern AI models boast impressive performance, they also require massive amounts of energy and resources for operation. This is further fuelling the research into AI-specific, optimised computing hardware. At the same time, the remarkable energy efficiency of the brain brings an interesting question: Can we further borrow from the working principles of biological intelligence to realise a more efficient artificial intelligence? This can be considered as the main research question in the field of neuromorphic engineering. Thanks to the developments in AI and recent advancements in the field of photonics and photonic integration, research into light-powered implementations of neuromorphic hardware has recently experienced a significant uptick of interest. In such hardware, the aim is to seize some of the highly desirable properties of photonics not just for communication, but also to perform computation. Neurons in the brain frequently process information (compute) and communicate using action potentials, which are brief voltage spikes that encode information in the temporal domain. Similar dynamical behaviour can be elicited in some photonic devices, at speeds multiple orders of magnitude higher. Such devices with the capability of neuron-like spiking are of significant research interest for the field of neuromorphic photonics. Two distinct types of such excitable, spiking systems operating with optical signals are studied and investigated in this thesis. First, a vertical cavity surface emitting laser (VCSEL) can be operated under a specific set of conditions to realise a high-speed, all-optical excitable photonic neuron that operates at standard telecom wavelengths. The photonic VCSEL-neuron was dynamically characterised and various information encoding mechanisms were studied in this device. In particular, a spiking rate-coding regime of operation was experimentally demonstrated, and its viability for performing spiking domain conversion of digital images was explored. Furthermore, for the first time, a joint architecture utilising a VCSEL-neuron coupled to a photonic integrated circuit (PIC) silicon microring weight bank was experimentally demonstrated in two different functional layouts. Second, an optoelectronic (O/E/O) circuit based upon a resonant tunnelling diode (RTD) was introduced. Two different types of RTD devices were studied experimentally:a higher output power, µ-scale RTD that was RF coupled to an active photodetector and a VCSEL (this layout is referred to as a PRL node); and a simplified, photosensitive RTD with nanoscale injector that was RF coupled to a VCSEL (referred to as a nanopRL node). Hallmark excitable behaviours were studied in both devices, including excitability thresholding and refractory periods. Furthermore, a more exotic resonate and-fire dynamical behaviour was also reported in the nano-pRL device. Finally, a modular numerical model of the RTD was introduced, and various information processing methods were demonstrated using both a single RTD spiking node, as well as a perceptron-type spiking neural network with physical models of optoelectronic RTD nodes serving as artificial spiking neurons.Over the last decade, we have witnessed an astonishing pace of development in the field of artificial intelligence (AI), followed by proliferation of AI algorithms into virtually every domain of our society. While modern AI models boast impressive performance, they also require massive amounts of energy and resources for operation. This is further fuelling the research into AI-specific, optimised computing hardware. At the same time, the remarkable energy efficiency of the brain brings an interesting question: Can we further borrow from the working principles of biological intelligence to realise a more efficient artificial intelligence? This can be considered as the main research question in the field of neuromorphic engineering. Thanks to the developments in AI and recent advancements in the field of photonics and photonic integration, research into light-powered implementations of neuromorphic hardware has recently experienced a significant uptick of interest. In such hardware, the aim is to seize some of the highly desirable properties of photonics not just for communication, but also to perform computation. Neurons in the brain frequently process information (compute) and communicate using action potentials, which are brief voltage spikes that encode information in the temporal domain. Similar dynamical behaviour can be elicited in some photonic devices, at speeds multiple orders of magnitude higher. Such devices with the capability of neuron-like spiking are of significant research interest for the field of neuromorphic photonics. Two distinct types of such excitable, spiking systems operating with optical signals are studied and investigated in this thesis. First, a vertical cavity surface emitting laser (VCSEL) can be operated under a specific set of conditions to realise a high-speed, all-optical excitable photonic neuron that operates at standard telecom wavelengths. The photonic VCSEL-neuron was dynamically characterised and various information encoding mechanisms were studied in this device. In particular, a spiking rate-coding regime of operation was experimentally demonstrated, and its viability for performing spiking domain conversion of digital images was explored. Furthermore, for the first time, a joint architecture utilising a VCSEL-neuron coupled to a photonic integrated circuit (PIC) silicon microring weight bank was experimentally demonstrated in two different functional layouts. Second, an optoelectronic (O/E/O) circuit based upon a resonant tunnelling diode (RTD) was introduced. Two different types of RTD devices were studied experimentally:a higher output power, µ-scale RTD that was RF coupled to an active photodetector and a VCSEL (this layout is referred to as a PRL node); and a simplified, photosensitive RTD with nanoscale injector that was RF coupled to a VCSEL (referred to as a nanopRL node). Hallmark excitable behaviours were studied in both devices, including excitability thresholding and refractory periods. Furthermore, a more exotic resonate and-fire dynamical behaviour was also reported in the nano-pRL device. Finally, a modular numerical model of the RTD was introduced, and various information processing methods were demonstrated using both a single RTD spiking node, as well as a perceptron-type spiking neural network with physical models of optoelectronic RTD nodes serving as artificial spiking neurons
Sites of Scottish heritage in translation : representing memory, history and culture for the French speaking visitor
Full text linkScotland boasts an extensive variety of castles, museums and other heritage sites which attract large numbers of domestic and international visitors each year. Such sites contribute significantly to the circulation of knowledge across linguistic and cultural borders and, in this context, interpretation (in the form of labels, wall panels, audio-guides, etc.) and interlingual translation play an essential role in ensuring that both domestic and international visitors can access and understand the past.This thesis is formed around a multiple case study carried out in six Scottish heritage sites. Focusing specifically on translations from English into French, the primary aim of this research project is to gain a better understanding of how translation choices can influence the experiences of French-speaking visitors and their overall perception of Scottish heritage. A secondary aim of the project is to get a better sense of the considerations which might drive or hinder translation provision for heritage bodies. This thesis thus explores heritage translation from three perspectives: (i) translation as a process, looking at the conditions under which translations are commissioned and produced; (ii) translation as a product, using Halliday’s model of Systemic Functional Linguistics (SFL) to identify translation shifts between source and target texts; and (iii) translation reception to discern whether and how language provision and translation shifts might impact the experience of visitors and their representation of Scottish cultural and historical heritage. Together, these three strands make it possible to pinpoint areas where translation is already well-utilised and well received and those where it can be improved, thus allowing the formulation of recommendations for best practice.Scotland boasts an extensive variety of castles, museums and other heritage sites which attract large numbers of domestic and international visitors each year. Such sites contribute significantly to the circulation of knowledge across linguistic and cultural borders and, in this context, interpretation (in the form of labels, wall panels, audio-guides, etc.) and interlingual translation play an essential role in ensuring that both domestic and international visitors can access and understand the past.This thesis is formed around a multiple case study carried out in six Scottish heritage sites. Focusing specifically on translations from English into French, the primary aim of this research project is to gain a better understanding of how translation choices can influence the experiences of French-speaking visitors and their overall perception of Scottish heritage. A secondary aim of the project is to get a better sense of the considerations which might drive or hinder translation provision for heritage bodies. This thesis thus explores heritage translation from three perspectives: (i) translation as a process, looking at the conditions under which translations are commissioned and produced; (ii) translation as a product, using Halliday’s model of Systemic Functional Linguistics (SFL) to identify translation shifts between source and target texts; and (iii) translation reception to discern whether and how language provision and translation shifts might impact the experience of visitors and their representation of Scottish cultural and historical heritage. Together, these three strands make it possible to pinpoint areas where translation is already well-utilised and well received and those where it can be improved, thus allowing the formulation of recommendations for best practice
Development of automatic time-domain simulation programme of berthing operation of ships
Full text linkAs the world trade has increased significantly over the past 50 years, safe and effective management of harbour system is becoming an important issue. In particular, due to the increased complexity of harbour environment with various harbour facilities, berthing operation of ships takes much time and requires various technical supports from harbour masters, pilots and engineers. In this point of view, precise prediction and practice of berthing operation are required and development of automatic simulation tool is requested for planning and managing effective harbour system.In this study, a novel methodology to control the heading angle and the speed of ships on the simulation of berthing operation is presented. Particularly under the low advance speed of a ship, the simulation of ship movement and the application of mathematical models are challengeable objectives in the current research field. Through this study, the development of two different time-domain simulation programs using the PD (Proportional Derivative) control and the MPC (Model Predictive Control) is performed with two different mathematical models which are the normal MMG model and Kose’s model. Furthermore, the model simulation is performed and the result is compared with previous works in different berthing conditions. With various cases of simulation result, the statistical analysis is performed for defining the initial environment of efficient berthing operation. This study is expected to provide an efficient time-domain simulation tool to harbour designers for planning and managing a harbour system cost-effectively and an opportunity to harbour masters and pilots for practicing and understanding the berthing operation in various harbour situations.To increase the accuracy on prediction of ship berthing operation, it is needed to analyse ship movement, in particular, with low advance speed and to develop an effective algorithm and controller for simulating the berthing operation accordingly.As the world trade has increased significantly over the past 50 years, safe and effective management of harbour system is becoming an important issue. In particular, due to the increased complexity of harbour environment with various harbour facilities, berthing operation of ships takes much time and requires various technical supports from harbour masters, pilots and engineers. In this point of view, precise prediction and practice of berthing operation are required and development of automatic simulation tool is requested for planning and managing effective harbour system.In this study, a novel methodology to control the heading angle and the speed of ships on the simulation of berthing operation is presented. Particularly under the low advance speed of a ship, the simulation of ship movement and the application of mathematical models are challengeable objectives in the current research field. Through this study, the development of two different time-domain simulation programs using the PD (Proportional Derivative) control and the MPC (Model Predictive Control) is performed with two different mathematical models which are the normal MMG model and Kose’s model. Furthermore, the model simulation is performed and the result is compared with previous works in different berthing conditions. With various cases of simulation result, the statistical analysis is performed for defining the initial environment of efficient berthing operation. This study is expected to provide an efficient time-domain simulation tool to harbour designers for planning and managing a harbour system cost-effectively and an opportunity to harbour masters and pilots for practicing and understanding the berthing operation in various harbour situations.To increase the accuracy on prediction of ship berthing operation, it is needed to analyse ship movement, in particular, with low advance speed and to develop an effective algorithm and controller for simulating the berthing operation accordingly
Survey-LAndings Model (SLAM) : a new length- based Bayesian method for stock-assessment
No full textFull analytical stock-assessment normally relies on age data, but that is not available for most species. Length data are cheaper to collect and is available for all species, and many modern models are being based on that. Length data can be gathered from different sources, for instance, the length distribution of the catches. An alternative source of time series data of length distribution is scientific surveys. Another source of information for species that are not aged is time series of biomass, for both catches and survey, as such can provide a valuable indication of total abundance. We developed a new length-based model that is able to incorporate data from different sources, survey, landings and discard, and data of two different types, length frequencies and time series of biomass. We called it the Survey-LAndings
Model (SLAM), it is based on a growth projection matrix and we fitted it using
the Bayesian package Rstan. The model is designed to be flexible and can respond to situations with different data availability. In this thesis it was tested in two versions, a “full model”, that fits survey length frequency and abundance, landings length frequency and abundance and discard abundance. The second version includes data from only survey length frequency and abundance. The two different versions are meant to reflect a situation with good data availability, where there is information about the catches and especially there is compositional information from the landings, and a highly data-limited situation, where the assessment can only rely on survey information. In the first research chapter (chapter III) we tested both versions on pseudo data, performed some sensitivity analysis and checked for bias. In the second research chapter (chapter IV) we applied the “full version” of SLAM to a data rich species: Whiting stock from division 6a. We evaluated its performance comparing it to an existent assessment and we assessed its sensitivity to specific assumptions. In the third research chapter (chapter V) we tested the “survey only” version, again we picked Whiting stock from division 6a as a data rich species, as well as Haddock from division 6a, and we compared the results with an existing assessment. In this chapter we applied SLAM to two data limited species from division 6a, which are Grey Gurnards and Lemon Sole. We conclude that SLAM can be a valid tool for stock assessment because it was able to produce assessments comparable to the ones produced by a well-established age-based stock assessment model, even by just using length information. Stocks like lemon sole and grey gurnard are currently un-assessed and there could be a
benefit for fisheries management of West of Scotland by the adoption of SLAM as a stock assessment tool.Full analytical stock-assessment normally relies on age data, but that is not available for most species. Length data are cheaper to collect and is available for all species, and many modern models are being based on that. Length data can be gathered from different sources, for instance, the length distribution of the catches. An alternative source of time series data of length distribution is scientific surveys. Another source of information for species that are not aged is time series of biomass, for both catches and survey, as such can provide a valuable indication of total abundance. We developed a new length-based model that is able to incorporate data from different sources, survey, landings and discard, and data of two different types, length frequencies and time series of biomass. We called it the Survey-LAndings
Model (SLAM), it is based on a growth projection matrix and we fitted it using
the Bayesian package Rstan. The model is designed to be flexible and can respond to situations with different data availability. In this thesis it was tested in two versions, a “full model”, that fits survey length frequency and abundance, landings length frequency and abundance and discard abundance. The second version includes data from only survey length frequency and abundance. The two different versions are meant to reflect a situation with good data availability, where there is information about the catches and especially there is compositional information from the landings, and a highly data-limited situation, where the assessment can only rely on survey information. In the first research chapter (chapter III) we tested both versions on pseudo data, performed some sensitivity analysis and checked for bias. In the second research chapter (chapter IV) we applied the “full version” of SLAM to a data rich species: Whiting stock from division 6a. We evaluated its performance comparing it to an existent assessment and we assessed its sensitivity to specific assumptions. In the third research chapter (chapter V) we tested the “survey only” version, again we picked Whiting stock from division 6a as a data rich species, as well as Haddock from division 6a, and we compared the results with an existing assessment. In this chapter we applied SLAM to two data limited species from division 6a, which are Grey Gurnards and Lemon Sole. We conclude that SLAM can be a valid tool for stock assessment because it was able to produce assessments comparable to the ones produced by a well-established age-based stock assessment model, even by just using length information. Stocks like lemon sole and grey gurnard are currently un-assessed and there could be a
benefit for fisheries management of West of Scotland by the adoption of SLAM as a stock assessment tool
Predicting the effectiveness of early senior decision-making in urgent internal medical care : application of a hybrid agent-based and discrete event systems simulation model to evaluate UK healthcare policy recommendations
Full text linkHospital systems face year-upon-year rises in demand for in-patient services. Moments when urgent care departments are overwhelmed with more patients than they are resourced to provide care for (overcrowding) frequently emerge due to poor availability of hospital beds. Policymakers and healthcare leaders in the UK recommend an early senior decision-making (ESDM) strategy to divert suitable patients away from in-patient services at the time of referral into urgent care. Policies also advise expert clinicians – the highest grade of clinical staff - should perform this task. This research specifically explored the effectiveness of the ESDM strategy when applied to urgent internal medical populations – the largest consumers of in-patient services – with the intention of informing a cost-effectiveness analysis of ESDM.
A systems simulation model (SSM) combining agent-based and discrete event systems simulation model was created to reproduce ESDM in a representative acute medical unit in the UK. Data to inform model conceptualisation, programming, and parameter inputs was gathered via observational ethnography, analytic autoethnography of expert early decision-making in urgent care, and prospective data collection of patient-reported outcomes. Outputs aligned with the goals of patients, staff, and provider goals were defined. Upon validation, the model was used to predict how outputs could change with different configurations of expert and non-expert staffing in the decision-maker role. Staffing strategies were analysed at increasing levels of tolerated overcrowding in the department to mimic high hospital occupancies that limited transfer from the unit. Modelled outputs were analysed for meaningful differences and trends.
Early senior decision-making realised meaningfully fewer moments of overcrowding and delays, but only when departmental overcrowding was enforced. This occurred via of intuitive decision-making by clinical experts - a phenomenon not previously reported in literature available at the time of writing. System-wide inefficiencies begin to emerge when experts perform decision-making for all patients referred. Impact upon patient health is unclear.
The ESDM strategy has the potential to realise safer in-patient care and generate local efficiencies in hospitals that face frequent moments of overcrowding, but not in systems that maintain urgent care bed occupancy levels below 100%. Improving currently available decision-support tools to harness the decision-making of experts may deliver efficiency gains at lesser cost. Further research into the health impact of admission avoidance and overcrowding in urgent care areas outside of the ED is warranted before cost-effectiveness may be explored.Hospital systems face year-upon-year rises in demand for in-patient services. Moments when urgent care departments are overwhelmed with more patients than they are resourced to provide care for (overcrowding) frequently emerge due to poor availability of hospital beds. Policymakers and healthcare leaders in the UK recommend an early senior decision-making (ESDM) strategy to divert suitable patients away from in-patient services at the time of referral into urgent care. Policies also advise expert clinicians – the highest grade of clinical staff - should perform this task. This research specifically explored the effectiveness of the ESDM strategy when applied to urgent internal medical populations – the largest consumers of in-patient services – with the intention of informing a cost-effectiveness analysis of ESDM.
A systems simulation model (SSM) combining agent-based and discrete event systems simulation model was created to reproduce ESDM in a representative acute medical unit in the UK. Data to inform model conceptualisation, programming, and parameter inputs was gathered via observational ethnography, analytic autoethnography of expert early decision-making in urgent care, and prospective data collection of patient-reported outcomes. Outputs aligned with the goals of patients, staff, and provider goals were defined. Upon validation, the model was used to predict how outputs could change with different configurations of expert and non-expert staffing in the decision-maker role. Staffing strategies were analysed at increasing levels of tolerated overcrowding in the department to mimic high hospital occupancies that limited transfer from the unit. Modelled outputs were analysed for meaningful differences and trends.
Early senior decision-making realised meaningfully fewer moments of overcrowding and delays, but only when departmental overcrowding was enforced. This occurred via of intuitive decision-making by clinical experts - a phenomenon not previously reported in literature available at the time of writing. System-wide inefficiencies begin to emerge when experts perform decision-making for all patients referred. Impact upon patient health is unclear.
The ESDM strategy has the potential to realise safer in-patient care and generate local efficiencies in hospitals that face frequent moments of overcrowding, but not in systems that maintain urgent care bed occupancy levels below 100%. Improving currently available decision-support tools to harness the decision-making of experts may deliver efficiency gains at lesser cost. Further research into the health impact of admission avoidance and overcrowding in urgent care areas outside of the ED is warranted before cost-effectiveness may be explored
Decarbonising heat and transport : impacts on local electricity systems
No full textThere is an increasing need to decarbonise both heating and transport sectors in the United Kingdom (UK), and the uptake of low carbon technologies (LCTs) will be central in achieving this. However, the uptake of LCTs is expected to pose significant planning and management challenges for distribution network operators (DNOs) in the coming decades as the impact of LCTs on electricity distribution networks varies both spatially and temporally, and is driven by the diversity in technology type, consumer behaviour, variable weather patterns, variation of the building stock and the incumbent network assets. In recognition of this diversity and household energy variability, LCT adoption and utilisation will be influenced by the distribution of socio-economic factors within a local area. This, in turn, has the potential to have varying impacts on distribution networks across different regions. Therefore, to inform decision making, and to ‘better’ quantify place-based LCT impact and the value of local flexibility, there is a requirement to understand the impact LCTs will have on distribution network infrastructure across diverse geographical areas with consideration for socio-technical and socio-spatial dimensions. This research, which is informed by unique access to distribution network infrastructure data for the entire north of Scotland, presents three approaches to explore key research questions within this theme, summarised as follows: 1. A high-resolution assessment methodology that enables assessment of electrified heat and transport impact on transformer headroom at scale using socio-economic indicators to inform the application of LCT consumption data. This includes mapping of spatially linked datasets to identify relationships between consumption and social deprivation. These relationships are then used as inputs to a heat pump (HP) modelling methodology that couples two methods of converting gas demand to equivalent electrical heat demand. This approach is compared with a generalised trial data approach to ascertain the impact of incorporating socio-economic elements. 2. A scalable approach to localised low voltage (LV) network and LCT impact modelling that couples two modelling methods: a LV network model development methodology and a LCT impact assessment methodology which accounts for both the electrification of heat and transport demand. The methodology extends the existing HP modelling method and similarly includes battery electric vehicle (EV) charging which is based on charging behaviour in the form of charging diaries showing the combined effect of different LCTs. This is demonstrated on spatially explicit LV network models through quantification of LCT network impact against key network assessment metrics. 3. A method to translate narratives on energy demand futures in heating and transport to impacts on local electricity systems, enabling quantification of the stress placed on key infrastructure and the ability of those demands to act ‘flexibly’ in supporting the renewables dominated generation mix necessary to achieve energy system decarbonisation at pace. The findings are considered from the perspective of the DNO and other key stakeholders to demonstrate the value in spatial and temporal high-resolution modelling, emphasising a need to consider the combined impact of electrified heat and transport in future network investment planning.There is an increasing need to decarbonise both heating and transport sectors in the United Kingdom (UK), and the uptake of low carbon technologies (LCTs) will be central in achieving this. However, the uptake of LCTs is expected to pose significant planning and management challenges for distribution network operators (DNOs) in the coming decades as the impact of LCTs on electricity distribution networks varies both spatially and temporally, and is driven by the diversity in technology type, consumer behaviour, variable weather patterns, variation of the building stock and the incumbent network assets. In recognition of this diversity and household energy variability, LCT adoption and utilisation will be influenced by the distribution of socio-economic factors within a local area. This, in turn, has the potential to have varying impacts on distribution networks across different regions. Therefore, to inform decision making, and to ‘better’ quantify place-based LCT impact and the value of local flexibility, there is a requirement to understand the impact LCTs will have on distribution network infrastructure across diverse geographical areas with consideration for socio-technical and socio-spatial dimensions. This research, which is informed by unique access to distribution network infrastructure data for the entire north of Scotland, presents three approaches to explore key research questions within this theme, summarised as follows: 1. A high-resolution assessment methodology that enables assessment of electrified heat and transport impact on transformer headroom at scale using socio-economic indicators to inform the application of LCT consumption data. This includes mapping of spatially linked datasets to identify relationships between consumption and social deprivation. These relationships are then used as inputs to a heat pump (HP) modelling methodology that couples two methods of converting gas demand to equivalent electrical heat demand. This approach is compared with a generalised trial data approach to ascertain the impact of incorporating socio-economic elements. 2. A scalable approach to localised low voltage (LV) network and LCT impact modelling that couples two modelling methods: a LV network model development methodology and a LCT impact assessment methodology which accounts for both the electrification of heat and transport demand. The methodology extends the existing HP modelling method and similarly includes battery electric vehicle (EV) charging which is based on charging behaviour in the form of charging diaries showing the combined effect of different LCTs. This is demonstrated on spatially explicit LV network models through quantification of LCT network impact against key network assessment metrics. 3. A method to translate narratives on energy demand futures in heating and transport to impacts on local electricity systems, enabling quantification of the stress placed on key infrastructure and the ability of those demands to act ‘flexibly’ in supporting the renewables dominated generation mix necessary to achieve energy system decarbonisation at pace. The findings are considered from the perspective of the DNO and other key stakeholders to demonstrate the value in spatial and temporal high-resolution modelling, emphasising a need to consider the combined impact of electrified heat and transport in future network investment planning
Battlefield tours to the former Western Front : what do young people experience?
Full text linkThis research uses qualitative methods to consider the experiences of twenty-eight young people during a visit to the former First World War battlefields of Belgium and France. Data was collected using participant diaries and semi-structured interviews, followed by a process of thematic analysis to identify themes in the young peoples’ written and verbal responses. Two themes were identified, analysed, and discussed, with relevant subthemes; Landscape (remembrance and commemoration): walking in the footsteps of others (a vicarious experience), understanding the war (a century removed), and duality of war and commemoration of the dead. Understanding death through the context of conflict: comprehension through empathy and face-to-face with human remains. The findings of this research suggest that young people who visit the former First World War battlefields of Belgium and France are likely to experience a form of emotional dissonance as they interpret and process the landscape(s); catalysed, in part, by their existing historical knowledge and understanding of what happened [from classroom learning] and their response to exploring these locations in the present day as commemorative sites. This research also suggests that there is, for educators, an opportunity to challenge conventional perceptions of conflict beyond existing popular narratives; as young people on battlefield tours are likely to shift from viewing the First World War from a nationalistic perspective to instead recognising it as a shared human experience. Lastly, this research acknowledges that for young people who participate in battlefield tours there is a contemplation of mortality, a deep introspection about loss and its resonance with their lives, families, and friends; an emotional impact that was compounded for the participants of this research when they were [unusually] witness to the recovery of First World War casualties at an archaeological dig.This research uses qualitative methods to consider the experiences of twenty-eight young people during a visit to the former First World War battlefields of Belgium and France. Data was collected using participant diaries and semi-structured interviews, followed by a process of thematic analysis to identify themes in the young peoples’ written and verbal responses. Two themes were identified, analysed, and discussed, with relevant subthemes; Landscape (remembrance and commemoration): walking in the footsteps of others (a vicarious experience), understanding the war (a century removed), and duality of war and commemoration of the dead. Understanding death through the context of conflict: comprehension through empathy and face-to-face with human remains. The findings of this research suggest that young people who visit the former First World War battlefields of Belgium and France are likely to experience a form of emotional dissonance as they interpret and process the landscape(s); catalysed, in part, by their existing historical knowledge and understanding of what happened [from classroom learning] and their response to exploring these locations in the present day as commemorative sites. This research also suggests that there is, for educators, an opportunity to challenge conventional perceptions of conflict beyond existing popular narratives; as young people on battlefield tours are likely to shift from viewing the First World War from a nationalistic perspective to instead recognising it as a shared human experience. Lastly, this research acknowledges that for young people who participate in battlefield tours there is a contemplation of mortality, a deep introspection about loss and its resonance with their lives, families, and friends; an emotional impact that was compounded for the participants of this research when they were [unusually] witness to the recovery of First World War casualties at an archaeological dig
Dysregulation of connexin-43 (cx43) in doxorubicin-induced cardiotoxicity
Full text linkThe chemotherapeutic drug doxorubicin (DOX) is widely used in the treatment of cancer; however patients experience dose-dependent cardiotoxicity that can manifest acute, early- and late-onset chronic and is associated with a decreased contractility and dilated cardiomyopathy. Similar effects have been reported during cardiac malfunction, which have been linked with a disorganisation and dysfunction of gap junctions called connexins in the heart. Here, we examine the effects of the anthracycline DOX on the expression and localisation of connexin-43 (Cx43) in rodent and human cardiac cells and cells of the vasculature to identify if drug treatment impacts this important cardiac connexin.
Through investigating the cardiotoxic effects of DOX, this project has shown that total Cx43 protein levels were reduced in human coronary artery endothelial cells (HCAECs), AC16 cardiomyocytes, human umbilical vein endothelial cells (HUVECs), and human cardiac fibroblasts (hCFs) in response to DOX. Interestingly, Langendorff perfusion of rat hearts with clinically relevant concentrations of DOX resulted in increased Cx43 expression in the left ventricle, with lateralisation of Cx43 in ventricular cardiomyocytes. Further investigation of these effects was explored using human 3D cardiac spheroids comprising HUVECs, hCFs, and iCell cardiomyocytes. Unlike the monolayer studies, Cx43 expression levels were not reduced when the cells were co-expressed in the 3D cell model. However, these spheroids were capable of spontaneous contraction and pilot studies using contractile 3D human iCell cardiomyocytes highlighted a change in contractility and calcium handling in spheroids in response to DOX.
Interestingly, parallel studies in cancer cells did not reveal significant changes in Cx43 expression in response to DOX, which may indicate that these effects are cardiac and vascular-cell specific. More recently, there has been a growing number of publications focusing on exosomal Cx43 as a biomarker for DOX-induced cardiotoxicity in cancer patients. The potential for indirect DOX effects on the heart mediated through the release of extracellular vesicles (EVs) from cancer cells is in its infancy as most studies have focussed upon direct drug effects on cardiac function. Nanoparticle tracking analysis of DOX-treated MDA-MB-231 cells did indeed result in significantly increased EVs released with no change in particle size (120-250nm). Challenges were experienced when investigating the exosomal Cx43 during DOX treatment therefore independent funding was secured during the PhD period to go on secondment to the Faculty of Medicine at University of Coimbra (FMUC) to work with Professor Henrique Girão, an expert in exosomal Cx43 biology during cardiotoxicity. During this period, molecular and cellular tools were optimised to permit the future study of Cx43 using their established Cx43 knock out and Cx43-GFP cell models. Establishing these models in Strathclyde Institute of Pharmacy & Biomedical Sciences (SIPBS), will now pave the way for more meaningful interrogation of the functional role of Cx43 doxorubicin-induced cardiotoxicity that was unfortunately beyond the timescale of the current investigation.
Collectively, the data generated in this thesis suggest that alterations in Cx43 protein expression and subcellular re-localisation, along with alterations in cardiomyocyte calcium handling may contribute to the detrimental effects of DOX on the heart. This research has ignited new venues for follow-up investigation of Cx43 at the molecular level to understand more fully the implications of the direct and indirect effects of DOX upon Cx43 expression, localisation and activity in the cancer and cardiac niche.The chemotherapeutic drug doxorubicin (DOX) is widely used in the treatment of cancer; however patients experience dose-dependent cardiotoxicity that can manifest acute, early- and late-onset chronic and is associated with a decreased contractility and dilated cardiomyopathy. Similar effects have been reported during cardiac malfunction, which have been linked with a disorganisation and dysfunction of gap junctions called connexins in the heart. Here, we examine the effects of the anthracycline DOX on the expression and localisation of connexin-43 (Cx43) in rodent and human cardiac cells and cells of the vasculature to identify if drug treatment impacts this important cardiac connexin.
Through investigating the cardiotoxic effects of DOX, this project has shown that total Cx43 protein levels were reduced in human coronary artery endothelial cells (HCAECs), AC16 cardiomyocytes, human umbilical vein endothelial cells (HUVECs), and human cardiac fibroblasts (hCFs) in response to DOX. Interestingly, Langendorff perfusion of rat hearts with clinically relevant concentrations of DOX resulted in increased Cx43 expression in the left ventricle, with lateralisation of Cx43 in ventricular cardiomyocytes. Further investigation of these effects was explored using human 3D cardiac spheroids comprising HUVECs, hCFs, and iCell cardiomyocytes. Unlike the monolayer studies, Cx43 expression levels were not reduced when the cells were co-expressed in the 3D cell model. However, these spheroids were capable of spontaneous contraction and pilot studies using contractile 3D human iCell cardiomyocytes highlighted a change in contractility and calcium handling in spheroids in response to DOX.
Interestingly, parallel studies in cancer cells did not reveal significant changes in Cx43 expression in response to DOX, which may indicate that these effects are cardiac and vascular-cell specific. More recently, there has been a growing number of publications focusing on exosomal Cx43 as a biomarker for DOX-induced cardiotoxicity in cancer patients. The potential for indirect DOX effects on the heart mediated through the release of extracellular vesicles (EVs) from cancer cells is in its infancy as most studies have focussed upon direct drug effects on cardiac function. Nanoparticle tracking analysis of DOX-treated MDA-MB-231 cells did indeed result in significantly increased EVs released with no change in particle size (120-250nm). Challenges were experienced when investigating the exosomal Cx43 during DOX treatment therefore independent funding was secured during the PhD period to go on secondment to the Faculty of Medicine at University of Coimbra (FMUC) to work with Professor Henrique Girão, an expert in exosomal Cx43 biology during cardiotoxicity. During this period, molecular and cellular tools were optimised to permit the future study of Cx43 using their established Cx43 knock out and Cx43-GFP cell models. Establishing these models in Strathclyde Institute of Pharmacy & Biomedical Sciences (SIPBS), will now pave the way for more meaningful interrogation of the functional role of Cx43 doxorubicin-induced cardiotoxicity that was unfortunately beyond the timescale of the current investigation.
Collectively, the data generated in this thesis suggest that alterations in Cx43 protein expression and subcellular re-localisation, along with alterations in cardiomyocyte calcium handling may contribute to the detrimental effects of DOX on the heart. This research has ignited new venues for follow-up investigation of Cx43 at the molecular level to understand more fully the implications of the direct and indirect effects of DOX upon Cx43 expression, localisation and activity in the cancer and cardiac niche
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