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Development of novel neurophysiological investigations for age-related muscle weakness
Full text linkPh. D. Thesis.No Abstract AvailableNIHR Newcastle Biomedical Research Centr
Observing and Theorising the Learning of Songwriting through Autoethnography
Full text linkPh. D. ThesisThis thesis contributes to the growing body of work on popular music songwriting pedagogy by developing a theory of songwriting praxis, from the position of practitioner-as-researcher.
The literature review draws primarily from scholarly material on creativity, and on popular music, which are discussed from within their respective domains to explore the scope of our current understanding of songwriting. I apply these works through the following thematic lenses:
• Authorship
• Imagined Audience
• Style
• Valuing in Songwriting
The methodology proposes a Merleau-Pontian phenomenological ontology of songwriting as a lived experience. This process is then developed through autoethnographic and reflective practice applied across a data collection, observation, and interview participant selection.
The five core chapters discuss the observation and theorisation, through the four lenses outlined above. In ‘Observations,’ autoethnographic reflections are presented as a naturally occurring narrative of developing a songwriting style. In the proceeding four chapters, these observations are then theorised in the context of the literature and triangulated with interviews from other songwriting practitioners. The theorising chapters are as follows: ‘Models of Authorship in Songwriting’, in which a model is constructed to depict the flow of authorship; ‘Identifying the Imagined Audience’, which describes how songs are written with an audience in mind using the songwriter’s ‘structuring knowledge’ – knowledge acquired from immersion in the domain, elsewhere referred to as Domain Acquired Knowledge; ‘Style and Voice’, balances the previous structuring knowledge with the songwriter’s creative agency; lastly, ‘Valuing in Songwriting’ focuses on how the previous concepts are applied in the context of the songwriter’s intentions. In the conclusion, the theories are contextualised within a systems model.
The outcome is a critical lens through which to observe and theorise how songwriting is learned rather than an epistemology of how to write songs. It is hoped that this approach will contribute to the pedagogy of songwriting
Exploring the role of endoplasmic reticulum stress in skeletal dysplasia
Full text linkPh. D. ThesisThe term skeletal dysplasia comprises a range of diseases that lead to varying
degrees of skeletal deformities, causing pain and reduction in quality of life. Whilst
each disease is typically rare, together they are estimated to occur in up to 1 of 5000
people. The intracellular retention of secreted proteins has been identified as one
common disease mechanism in several skeletal dysplasias, including
pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (MED). Yet, the
specific pathways that are involved may be mutation-, gene- or disease-specific, or
subject to disease modifiers and thus require specific treatments.
Several approaches to study skeletal dysplasia and the resulting endoplasmic
reticulum stress in vitro, including the use of human induced pluripotent stem cells
(hiPSCs), were evaluated. HT1080 fibrosarcoma cells overexpressing wild type and
mutant p.D469del COMP were validated as an in vitro model system for PSACH
before performing RNA sequencing and DNA methylation analysis. Additionally,
several mutant COMP constructs were overexpressed in HT1080 cells to study a
potential common mechanism of COMP-MED and PSACH.
Whilst hiPSCs offer exciting opportunities for the in vitro study of skeletal diseases,
high variation during differentiation protocols rendered them unsuitable for this study.
DNA methylation analysis revealed an unexpectedly large number of differentially
methylated CpG sites, whilst RNA sequencing of D469del COMP cells revealed an
increase in inflammatory signalling, and a marked upregulation of MMP9 and
GALNT18. Elevated MMP9 expression correlated with increased extracellular MMP9
activity. This was also found in cell lines overexpressing other disease-causing
COMP proteins, but not in a cell model of MATN3-MED.
The data presented in this thesis indicates that COMP mutations act via a common
mechanism that is distinct from MED-causing mutations in MATN3. It also provides
evidence that MMP9 could be a marker for COMP-caused stress in vitro and thus
facilitate future drug screenings.MCDS therapy project, RUBICON networ
The effect of intrinsic and extrinsic influences on skin ageing within associated demographics
Full text linkPh. D. ThesisThe skin ages because of intrinsic and extrinsic influences, resulting in damage to mitochondrial DNA (mtDNA). Intrinsic ageing occurs chronologically and cannot be controlled; however,
extrinsic skin ageing results from exposure to environmental factors such as ultraviolet radiation
(UVR). Although only reported in a small number of publications, previous studies have used
a skin swab technique to detect differences in mtDNA damage as a result of UVR exposure.
Limited repair mechanisms make mtDNA an effective biomarker of ageing, pioneered
predominantly by the Birch-Machin laboratory.
A plasmid containing a mitochondrial region of interest was developed to improve normalisation methodology for mtDNA damage comparison. A VISIA® Skin Analysis system was also used to investigate UV spot variation, which was used alongside the swab technique to determine whether differences in mtDNA damage following recent UVR exposure and
lifestyle factors can be detected using a skin swab, including a large seasonal study (n=87).
Although forskolin and caffeine are natural compounds frequently used in the cosmetic industry, their combined effect has not been investigated; therefore, their protective effects
against complete solar light in human dermal neonatal fibroblasts (HDFn) was investigated
using cell viability assays.
We built upon previous research involving the skin swab by investigating differences in
mtDNA damage between individuals. Results did not show a consistent increase in damage immediately following high intensity UVR exposure and significant correlations were not observed with sun exposure and protection behaviours. A seasonal study showed the greatest level of mtDNA damage in spring, in comparison to summer and autumn and a significant positive corelation was seen between protection behaviours and mtDNA damage in swabs collected from the left cheek in summer (p=0.02). UV spot %Area increased during summer
and decreased during winter, and trends were observed with age and skin type. A trending
correlation was observed between mtDNA damage and UV spots in samples collected from the right side of the face in spring (p=0.09). A combination of caffeine and forskolin was found to
have protective effects against 4.32 standard erythemal dose (SED) complete solar light.
Although mtDNA damage observed did not reflect perceived recent UVR exposure under our
experimental study protocol, facial imaging analysis showed some correlations; however,
further studies are necessary. Future studies would employ an objective measure of sunscreen
use which would enable a clearer conclusion. Facial imaging analysis could not only prove
effective at measuring damage, but could also be useful in the screening of protective skincare compounds such as forskolin and caffeine.European Regional Development Fun
A Conceptualization of the Role of Economic Characteristics in Resources Conservation: An Application to the Study of Work Engagement
Full text linkPh. D. Thesis.This thesis examines the resources conservational effect of two economic life experiences,
namely, economic life demands and organisational experiences of economic adversities on
work engagement. Despite the acknowledgement of the relevance of economic resources in
the acquisition and sustainment of emotional resources, little is known regarding whether and
through what mechanism do economic life experiences relate with work engagement. Having
a conceptual account that highlights the theoretical underpinnings of economic life
experiences in relation to work engagement is crucial for the development of workplace
interventions that can help sustain work engagement particularly during periods of economic
constraints at both the individual and organisational level.
To address this gap, two empirical studies were conducted. Specifically, it was examined
whether i) economic life demands and ii) organisation experiences of economic adversities
relate adversely with work engagement, and if yes, why and under what conditions will this
relation be salient. In addressing these questions, this thesis drew from the conservation of
resources theory. Using a three-wave (approximately one week apart) panel data set (N= 145),
this thesis finds that i) employees’ economic life demands and ii) organisational experiences
of economic adversities relates negatively to work engagement.
Moreover, analyses of mediation relationship showed that economic life demands relate
negatively and indirectly with work engagement through the mediating effects of emotional
distress. Likewise, it was found that organisational experiences of economic adversities relate
negatively and indirectly with work engagement through (i) role ambiguity and (ii)
organisational support for strength use. Analysis of moderation-mediation relationship
elucidated that that off-job detachment mitigated the detrimental influence of economic life
demands on work engagement through emotional distress such that the strength of the adverse
influence was less under conditions of high economic life demands and high off-job
detachment. Furthermore, results of moderation-mediation analysis revealed that detachment
buffered the indirect negative influence of organisational experiences of economic adversities
on work engagement. Specifically, it was discovered that the mediating influence of role
ambiguity and organisational support for strength use was less salient under conditions of
high organisational experiences of economic adversities and high detachment.
The thesis’s findings that economic life demands relate negatively with work engagement
through emotional distress help substantiate the desperation and resource loss spiral principle
iv
of the conservation of resources theory. Likewise, findings of this thesis, in particular, the
conditioning influence of detachment in the indirect relation between economic life demands
and work engagement provides support for the resource passageways principle of the
conservation of resources theory. Furthermore, the negative indirect influence of
organisational experiences of economic adversities on work engagement through role
ambiguity and organisational support for strength use substantiate that the desperation
principle of the conservation of resources theory at the level of the organisation. From a
practitioner perspective, findings of this thesis demonstrate that intervention measures that are
centred towards the promotion of off-job detachment is a core medium through which
organisations can promote employee work engagement
Image-informed numerical modelling of particulate systems with irregular grains
Full text linkPhD ThesisGranular materials are everywhere around us. Their omnipresence makes our interaction with them on a daily basis a certainty, and yet our understanding of their
mechanical behaviour is far from complete. Regarding geotechnical applications,
most natural granular materials, such as silts, sands, gravels and ballast, feature
irregular particle shapes, a fact that makes their mechanical behaviour all the more
complex across scales, from micro to meso and macro. A multitude of experimental
and numerical studies have demonstrated the importance of particle morphology in
the shear strength of particulate materials, although rarely demonstrating a direct
link or mechanisms of causality between them. This is mainly due to the high complexity of the problem but also partially due to the lack of intelligible and accessible
tools to quantify the morphology of three-dimensional irregular particles.
This thesis aims to contribute to the current state-of-art studying the characterisation of granular materials by providing analytical and numerical tools for shape
characterisation. Regarding analytical tools, this thesis attempts a critical review
of existing indices to characterise and classify particle form, while introducing a
new set of indices. Regarding numerical tools, this thesis provides novel software
solutions for automatic particle shape characterisation and for the generation of
image-informed numerical models. These open-source tools are meant to shed light
on the inherent subjectivity of performing shape characterisation on a practical level.
Regarding the generation of numerical models based on imaging data, algorithmic
implementations are offered to create simplified polyhedra and multi-sphere particles at user-defined fidelity levels of resolution, the morphology of which can also be
characterised and compared to that of the original fidelity level.
Combining the produced analytical and numerical tools, this thesis demonstrates
a seamless workflow between particle imaging data and numerical modelling, using
the discrete element method and non-spherical particles. This workflow is utilised
to develop a methodology for the generation of Representative Element Volumes
(REVs) of non-spherical particles, which represent the polydispersity of both particle size and shape, aiming to link quantitative morphology characterisation at the
particle scale and mechanical characterisation at the level of a representative assembly of particles. The methodology is then applied to systematically generate REVs
of railway ballast using image-informed multi-sphere particles of various levels of
simulation fidelity, allowing for a parametric study of the effect of several modelling
parameters on the shear strength of the material
Technology at work and domestic labour: A critical exploration of gender, class, and work-life articulation
Full text linkPh. D. Thesis.This thesis explores how reproductive and other domestic labour is managed in work time through personal internet use at work [PIUW]. For parents, PIUW makes it possible to be available to children during the workday and to receive communications from school and nursery. It allows life projects to be managed across the work-life boundary. Managing life projects in work time has widespread wellbeing benefits. However, it is clear from empirical data that technology is not universally enabling in the contemporary office. Analysis of 44 interviews with office workers and managers reveals a dramatic inequality between those in working-class and middle-class jobs. Overall, this study finds that the PIUW of those in working-class jobs is constrained (limiting their ability to manage life-related tasks) while the PIUW of those in middle-class jobs is enabled (allowing them to manage life-related tasks). Furthermore, women in middle-class jobs are significantly more likely than women in working-class jobs to use PIUW instrumentally, to manage home-related tasks. To explain findings, this thesis develops a realist intersectional comparison of gender and occupational class that supports a critical explanation of the interplay between agency and structure through which observed differences in PIUW, relationships between phenomena such as norms, workplace rules, and individual beliefs are explored. Two elements of Lawson’s ontological framework are drawn on. These are Lawson’s (2012) theory of social positioning and Lawson’s (2003) method of contrastive explanation. As a result, an original theoretical contribution is developed via a theoretical model of positionality created from the abductive analysis. The model makes it possible to explain how class manifests itself through the labour process leading to several contributions. Firstly, an explanation is developed of how it is that one group of workers is relatively disadvantaged regarding PIUW. Secondly, through tracing relationships between labour process conditions and collective rule-following practices, an explanation is developed of how inequality is inscribed at multiple levels through the operation of organisational power. Thirdly, by comparing the work-life experiences of those in different labour market positions this research contributes to debates around work-life and inequality, that are otherwise overly focused on the experience of the middle clas
Bond graph modelling of exergy in integrated energy systems
Full text linkPh. D. Thesis.Integrated municipal or district energy systems are one facet of the effort to support
sustainable energy systems that work towards reducing anthropogenic climate change
emissions. Current energy systems — including electricity, heat, and cooling — operate mostly independently, under the control of domain-distinct industries and regulatory
bodies. Operating these separate systems in a cooperative or integrated manner promises
improvements in efficiency, the ability of networks to absorb renewable energy sources
and storage, emissions reductions and community-based benefits.
The nature of district energy systems is that they cannot easily be modified or built
upon without severe disruption to the communities they serve, so assessments of their
behaviour and performance caused by potential changes must be modelled. This thesis
investigates what methods can model integrated energy systems and develops a bond
graph-based approach to constructing a fully-integrated system model. Although energy
based methods for integrated energy system modelling exist, this thesis demonstrates that
exergy can form the basis of integrated energy system models. Exergy being a measure
of the usefulness of energy allows the equivalence of energy domains in a single model
form, permitting development of a genuine, physically-founded integrated energy system
model.
An integrated model of a residential district supplied by heat and electrical networks,
based on a real UK urban area, is demonstrated in OpenModelica using the developed
modelling approach. The concept of an exergy storage device is introduced to provide
a mechanism for mediating energy flows between the networks. The model is used to
evaluate the performance of the test network, using trial cases to investigate how transferring exergy between energy domains through the mediating storage affects the overall
system energy and exergy efficiencies. Operational regimes that transfer energy from the
electrical to the thermal sub-system using the mediating storage are found to improve the
exergy efficiency of the system.Newcastle University, Siemen
Decentralised, trustless marketplace for brokered IoT data trading
Full text linkPhD ThesisTrading data as valuable assets has become a trend. The use of real-time data generated
from IoT devices provides a new insight into how to conduct a profitable business. As data
marketplaces are becoming ubiquitous, it is also becoming clear that IoT data hold value for
potential third-party consumers. This work introduces a marketplace for IoT data streams
that can unlock such potential value in a scalable way, by enabling any pairs of data providers
and consumers to engage in data exchange transactions without any prior assumption of
mutual trust. It investigates the use of the power of blockchain technology in automating
data trade agreements in a decentralised architecture. We present a marketplace protocol to
support trading of streaming data, from the advertising of data assets and the stipulation of
legally binding trading agreements, to their fulfilment and payment settlement, and managing
trade participants’ reputations. This work has two outcomes: a marketplace model and a
reputation model. We present a decentralised, trustless marketplace for brokered IoT data
trading, using Blockchain in Ethereum network that enables producers and consumers to
start trading in the absence of trust; however, it is managed by a reputation model. Our
marketplace is powered by a reputation system that is designed to address participants’ trust
and the reputation management of these traders in this marketplace. We mathematically
define the reputation model by applying a reputation function to the marketplace participants –
either producers or consumers – to quantify their trustworthiness in trading, based on various
criteria. We evaluate the marketplace functionalities and its reputation model by designing
a marketplace simulator. It is designed to simulate participant trading in the marketplace
and how reputations are quantified based on rules and criteria defined in the system protocol.
It is configured to replicate the behaviour of multiple pairs of producers and consumers
in different trading scenarios and show how reputations are measured in these different
scenarios. We experimentally show the trade-off between a trade overhead cost and the level
of participant trust. On Blockhain Ethereum Mainnet, our system evaluates the latency of
transactions an Ethereum takes to process and confirm our marketplace transactions
Real-time performance diagnosis and evaluation of big data systems in cloud datacenters
Full text linkPhD ThesisModern big data processing systems are becoming very complex in terms of largescale, high-concurrency and multiple talents. Thus, many failures and performance
reductions only happen at run-time and are very difficult to capture. Moreover, some
issues may only be triggered when some components are executed. To analyze the root
cause of these types of issues, we have to capture the dependencies of each component
in real-time.
Big data processing systems, such as Hadoop and Spark, usually work in large-scale,
highly-concurrent, and multi-tenant environments that can easily cause hardware and
software malfunctions or failures, thereby leading to performance degradation. Several systems and methods exist to detect big data processing systems’ performance
degradation, perform root-cause analysis, and even overcome the issues causing such
degradation. However, these solutions focus on specific problems such as stragglers and
inefficient resource utilization. There is a lack of a generic and extensible framework
to support the real-time diagnosis of big data systems.
Performance diagnosis and prediction of big data systems are highly complex as these
frameworks are typically deployed in cloud data centers that are large-scale, highly
concurrent, and follows a multi-tenant model. Several factors, including hardware
heterogeneity, stochastic networks and application workloads may impact the performance of big data systems. The current state-of-the-art does not sufficiently address
the challenge of determining complex, usually stochastic and hidden relationships between these factors.
To handle performance diagnosis and evaluation of big data systems in cloud environments, this thesis proposes multilateral research towards monitoring and performance
diagnosis and prediction in cloud-based large-scale distributed systems by involving a
novel combination of an effective and efficient deployment pipeline.The key contributions of this dissertation are listed below:
- i -
• Designing a real-time big data monitoring system called SmartMonit that efficiently collects the runtime system information including computing resource
utilization and job execution information and then interacts the collected information with the Execution Graph modeled as directed acyclic graphs (DAGs).
• Developing AutoDiagn, an automated real-time diagnosis framework for big data
systems, that automatically detects performance degradation and inefficient resource utilization problems, while providing an online detection and semi-online
root-cause analysis for a big data system.
• Designing a novel root-cause analysis technique/system called BigPerf for big
data systems that analyzes and characterizes the performance of big data applications by incorporating Bayesian networks to determine uncertain and complex
relationships between performance related factors.
The key contributions of this dissertation are listed below:
- i -
• Designing a real-time big data monitoring system called SmartMonit that efficiently collects the runtime system information including computing resource
utilization and job execution information and then interacts the collected information with the Execution Graph modeled as directed acyclic graphs (DAGs).
• Developing AutoDiagn, an automated real-time diagnosis framework for big data
systems, that automatically detects performance degradation and inefficient resource utilization problems, while providing an online detection and semi-online
root-cause analysis for a big data system.
• Designing a novel root-cause analysis technique/system called BigPerf for big
data systems that analyzes and characterizes the performance of big data applications by incorporating Bayesian networks to determine uncertain and complex
relationships between performance related factors.
The key contributions of this dissertation are listed below:
- i -
• Designing a real-time big data monitoring system called SmartMonit that efficiently collects the runtime system information including computing resource
utilization and job execution information and then interacts the collected information with the Execution Graph modeled as directed acyclic graphs (DAGs).
• Developing AutoDiagn, an automated real-time diagnosis framework for big data
systems, that automatically detects performance degradation and inefficient resource utilization problems, while providing an online detection and semi-online
root-cause analysis for a big data system.
• Designing a novel root-cause analysis technique/system called BigPerf for big
data systems that analyzes and characterizes the performance of big data applications by incorporating Bayesian networks to determine uncertain and complex
relationships between performance related factors.State of the Republic of Turkey and the Turkish Ministry
of National Educatio