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The development of ToF-SIMS for in-situ glycosaminoglycan analysis
No full textGlycosaminoglycans (GAGs) are linear polysaccharide chains composed of repeating disaccharide units with essential roles in several biological processes from embryonic patterning to modulation of blood vessel permeability. Despite their biological importance, GAG analysis is limited by a lack of available tools that can provide simultaneous spatial and compositional analysis. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a method of mass spectrometry imaging that enables the collection of compositional analysis through the generation of mass spectra, and spatial analysis through the conversion of spectra to an image. Previous utilisation of ToF-SIMS for in-situ GAG analysis has focussed on sulphate-containing ions that provide minimal compositional information.
In the approach presented here, a series of knockout cells lines mutant for components of the GAG biosynthetic pathway are analysed to generate and validate a library of SIMS ions that discriminate between different GAG types, including both sulphated and non-sulphated. These ions were acquired from biological samples that contain a milieu of biomolecules. Through the analysis of cell lines carrying knockouts of specific sulphotransferases, ions were identified that were discriminatory of both heparan sulphate (HS) and chondroitin sulphate (CS) sulphation modifications. To the best of our knowledge, this is the first example of the use of knockout cell lines to validate the likely biological origin of a SIMS ion.
Methods of multi variant analysis were optimised to enable the use of ions non-discriminatory of individual GAG types to act as an initial screening tool to identify GAG related changes in samples. Principal component analysis and partial least square regression discriminant analysis could use the intensity of such ions to discriminate between wild type (WT) and GAG synthetic mutant cell lines.
Ions identified in cellular samples were then applied to more complex tissue and used to investigate spatial and compositional changes in GAGs occurring in pathology. A particular focus was placed on understanding GAG related changes in renal tissue, including in diabetes, Alport syndrome and pregnancy. SIMS could identify the well-known loss of HS in diabetes and identified a previously unknown change in CS sulphation that occurs in WT pregnant mice but not Alport syndrome pregnant mice and could provide a potential mechanism for the exacerbated proteinuria observed during an Alport syndrome pregnancy. A workflow to use SIMS as a method of measuring endothelial glycocalyx (eGX) thickness was established to enable simultaneous spatial and compositional analysis of the carbohydrate rich layer, which is not possible using current techniques. Finally, high resolution SIMS images of human glomeruli were acquired. Again, to the best of our knowledge this is the first example of such analysis. A workflow was generated to identify GAG ion intensity changes over the individual layers of the glomerular filtration barrier to improve the understanding of where specifically within the barrier GAG related changes occur in pathology.
This thesis presents the development of ToF-SIMS as a method of in-situ GAG analysis that overcomes several limitations to enable label free, simultaneous spatial and compositional analysis. The technique is uniquely positioned to improve our understanding of fundamental GAG biology. SIMS can be used to investigate and identify relationships between different GAG types, including in-situ analysis of GAGs where their function remains poorly understood, such as in human embryonic development. Furthermore, SIMS can be used to discriminate the spatial distribution and composition of GAGs between healthy and disease state samples, including liquid and tissue biopsies, enabling improved understanding and detection of these complex molecules, potentially identifying new diagnostic and therapeutic targets
Semiconductor and Circuit Modelling Methods for Next Generation RF Receiver Protection Devices
Full text linkThis thesis explores modelling a receiver protector system (RxP) in un precedented detail. Using the UTLM method and software developed at the University of Nottingham by Prof. Phil Sewell and Prof Ana Vukovic, the research presented in this thesis uses detailed simulations to initially explore the effects of adding some of the key components in a piecewise manner. Predictably, the inclusion of the inductive post has the most significant impact on the performance, with the diameter of the post varied and investigated, along with the diameter of the upper boss and lower cavity and the depth of protrusion for both the upper boss and lower cavity. Furthermore, a detailed analysis of the PiN diode model structure is presented. Progressing the model of the diode from a solid metallic block with simple behaviour, to a model of a silicon PiN diode where each of the 3 layers is defined individually, it is hoped that this final model can then be the foundations for further research into the semiconductors that drive RxP systems. Finally, an exploration into the scattering effects of the RxP system is presented. The inductive post has the capability of scattering the incident signal, some of which excite modes with higher cut-off frequencies. Which modes are excited and what criteria they most fulfil are also considered. The scattering into higher order modes presented in this research is an as yet unexplored area of study in electromagnetic simulation work. i The results presented here offer an insight into the behaviour of the RxP system above the desired operating band and indicate what happens to the “lost” power at higher frequencies. This research was impacted by the 2020 COVID-19 Pandemic, with restrictions in the UK limiting access to required infrastructure and reducing the collaboration opportunities with some stakeholders. Furthermore, as this research is based around modelling a practical system, commercial sensitivities have mean that some parameters have been modified and other elements remain unpublished to protect the IP of the industry ad visors. Nonetheless, the data presented in this thesis provides a detailed analysis of specific elements of the RxP, a detailed development of the PiN diode model and an interesting exploration of the scattering effects of the RxP at frequencies higher than the operating band, and how the response of the system at these frequencies is similar to that of a high-pass filter
The impact of environmental, social, and governance (ESG) factors on firm financial performance and stock prices: evidence from the FTSE Bursa Malaysia Emas index (FBMEMAS)
No full textThis dissertation examines the impact of ESG ratings on firm financial performance and stock prices among companies listed on the FBMEMAS Index from 2021 to 2023. ESG ratings are sourced from FTSE Russell, while financial performance is measured using ROA and ROE. Stock price performance is assessed based on the closing stock price at the end of each financial year.
The findings indicate that ESG ratings have no statistically significant relationship with financial performance, aligning with Atan (2018). However, ESG ratings show a negative relationship with stock prices, suggesting that investors may perceive ESG adoption as an additional cost burden, leading to lower stock price. This supports existing literature suggesting that while ESG investments may not yield immediate financial benefits, they can shape investor sentiment and contribute to long-term value creation (Gibson et al., 2020; Nirino et al., 2021).
A quantitative research approach is employed, using panel data regression models to address econometric concerns. The study applies Pooled Ordinary Least Squares (POLS), Fixed Effects (FE), and Random Effects (RE) models. Diagnostic tests, including the Breusch-Pagan heteroskedasticity test and the Hausman test, confirm the FE model as the most appropriate, effectively controlling for firm-specific heterogeneity and mitigating biases. The results validate that ESG ratings negatively impact stock prices but have no significant effect on ROA and ROE. These findings align with prior research suggesting that ESG adoption in emerging markets does not deliver immediate financial returns due to regulatory and structural challenges (Buallay, 2019; Lee et al., 2023).
This study contributes to the ESG-financial performance debate in emerging markets by providing empirical evidence from Malaysia. The findings highlight the need for firms to balance ESG commitments with financial objectives to align with investor expectations and regulatory requirements. Policymakers should enhance ESG disclosure standards to improve transparency and build investor confidence. Future research could explore long-term financial implications to provide a more comprehensive understanding of ESG adoption in Malaysia
Protecting heritage by quantifying the thermal comfort benefits of traditional adobe buildings in Ilorin, Nigeria
Full text linkTraditional adobe buildings are often recognized for their lower environmental impact and responsiveness to climate. However, they can be susceptible to erosion and damage caused by exposure to weather conditions, and their maintenance can be laborious and reliant on craft skills passed on through generations. Therefore, they can fall into disrepair and/or replace parts with less laborious materials that may impact their performance. In this work, interventions focused on improving performance and optimizing building fabric to ensure occupant comfort were explored to help safeguard these culturally significant buildings from extinction.
In Nigeria, the usage of adobe material is widely spread in areas where there is a shortage of construction materials and/or limited access to modern building techniques. The country has a wealth of heritage adobe buildings, with their characteristics responding to ethnical diversity. The assessment of these buildings has gained increasing interest among researchers in Nigeria, driven by concerns about their rapid deterioration and erosion despite their cultural value. In this study, the author has quantified the ability of traditional adobe buildings to provide thermal comfort through four main case studies based on the tropical savanna climate of Ilorin City (latitude 8.5°N, longitude 4.45°E), which is warm and humid all year. A multi-method approach combining qualitative and quantitative methodologies was taken, and it included a series of occupant surveys, interviews, in-situ measurements, and computer simulation analysis. Four existing traditional Adobe residential building designs, with various layouts, courtyard systems, plan configurations, forms, and shapes, were characterized to assess their distinct cultural aspects and investigate their suitability for performance improvement alongside conservation.
Survey findings indicated that 91% of the occupants were satisfied with the indoor thermal living conditions, and this also gave insights into the cultural value, attachment, and sense of belonging of Ilorin people. The in-situ monitoring has revealed that the standard effective temperature (SET) point was 28.7 °C while the lower and upper indoor temperatures were 25.2 and 32.1 °C, respectively, which surpassed the temperature range (22 – 27 °C) for naturally ventilated residential buildings by a standard for the tropical warm-humid climate. These findings were used to produce dynamic simulation models that enabled the exploration of the impact of the materials on comfort. The simulation analysis revealed that the original (as-built) building was within comfort for 65 % of the time compared to 59 % for the current as-occupied buildings. However, when heritage-sensitive strategies were applied to create an improved/optimized building, the spaces were within comfort for 81 % of the time. Based on the findings, a maintenance, performance, and improvement framework were developed with practical recommendations for preserving and enhancing traditional Adobe buildings. The results were used to shape a framework to inform Nigerian policymakers, architects, builders, and occupants to improve the adoption of best practices for adobe construction in warm-humid climates and help protect their heritage
The mobility and dissemination of blaOXA-48 and blaNDM carbapenemase genes within clinical Escherichia coli isolates
Full text linkThe spread of antimicrobial resistance within the global population is a matter of serious concern with extensive impacts, but there is a particular severity to disproportionately of resistance spread within hospital settings. These settings act as hotspots and epicentres for the generation and dissemination of a sleugh of antibiotic-resistant bacteria. The environment of high antibiotic use, high concentration of infected individuals or immunocompromised individuals and the frequency of exposure to external bacteria through catheters and IVs etc, provides the ideal environment for the development of multidrug resistant bacterial isolates with unprecedented resistance to commonly applied clinical antibiotics and mechanisms of gene mobility.
A particular concern is the rise of resistance towards the carbapenem class of antibiotics which are considered antibiotics of last resort, only used in the most severe of infections. As the strength of resistances increase however, so does the use of these carbapenems, which has resulted in a steep increase in the cases of carbapenem resistant bacteria being observed. The production of the prolific NDM and OXA-48-like enzymes in bacteria has conferred concerning resistance to carbapenems and the genes that encode for them are frequently observed on plasmids bearing the ability to transfer themselves between bacteria of the same and different species and plasmids containing mobile genetic elements that can transfer them into more mobile plasmids.
The goal of this research is to examine the varieties of these carbapenem resistance genes in E. coli isolates collected from patients in a hospital setting and to identify the subtypes of NDM and OXA-48 that dominate in the bacterial population within the hospital, and which features of the plasmids are shared through them to form an idea of the phylogeny. This snapshot of data from a clinical setting can then be used as an insight into the state of carbapenem resistance in the UK as a whole
Topics in half integral weight modular forms
Full text linkThis thesis is divided in three independent chapters. In chapter 1, we prove some explicit results concerning images under Shimura’s map, the methods are elementary. In chapter 2, we provide results on two kernels of half integral weight. Chapter 3 is an exposition to the results obtained as part of the collaboration with Wissam Raji, Larry Rolen and one of my supervisors Nikolaos Diamantis, where we study periods in the half integral weight setting
Axial compressive testing of concrete-filled steel tubular members incorporating demolished concrete lumps
No full textCompound concrete (CC) can be cast by mixing fresh concrete (FC) with coarsely crushed demolished concrete lumps (DCLs) that have been obtained from a demolished structure. DCLs are larger than recycled concrete aggregates and are treated as a whole concrete replacement instead of a coarse aggregate replacement. This distinction implies that CC uses less Portland cement in comparison to FC, which reduces the embodied carbon of this material. A significant challenge for the broader application of CC is the lower compressive strength and ductility stemming from the weak interface between the DCLs and surrounding FC. However, the use of CC in concrete-filled steel tubes (CFSTs) and concrete-filled stainless-steel tubes (CFSSTs) has the potential to mitigate this issue due to the lateral confinement provided by the steel tube. Furthermore, the use of CFSST members is particularly favourable in corrosive conditions such as marine environments due to the material properties of stainless-steel.
The environmental benefits of using CC coupled with the lack of comprehensive research motivated the development of this research project at the University of Nottingham. The experimental investigation initially evaluates the compressive behaviour and strengths of 96 CC test specimens, including both 150 mm-sided CC cubes and 150×300 mm CC cylinders. A novel design equation that predicts the compressive strength of CC is derived using the data generated in this study and the data obtained from six previous studies in the literature. The proposed design equation is shown to be more accurate than the existing compressive strength equation proposed in previous studies. The experimental investigation also studies the compressive behaviour of circular CFST members, square CFSST members and rectangular CFSST members. The axial capacity of the CFST and CFSST members are predicted using the European Code (EC4), American Specification (AISC360) and Chinese Code (DBJ13-51). The continuous strength method is also used herein as a modification to EC4, which provides a more accurate prediction of the design strength of stainless-steel by modelling the strain hardening effect. Finally, the applicability of the considered design codes is evaluated by comparing the predicted axial capacities to the experimental failure loads
Integrated DC-DC converter topologies for electric vehicle applications
No full textThe current practice in electric vehicles (EVs) is to use two separate converters i.e., the on-board charger (OBC) and the auxiliary power module (APM), to charge the EV high-voltage (HV) and low-voltage (LV) batteries. In this thesis,
the integration of the OBC and APM in a single multiport converter topology is investigated. The proposed architecture aims to reduce the overall volume and component count of the EV charger, as well as improve the charger’s efficiency.
Towards this direction, two different three-port isolated DC-DC converter topologies are investigated in this research and their performance for integrated on-board charger (IOBC) application is evaluated. First, the topology of the triple-active-bridge (TAB) converter is analyzed and a methodology to estimate the converter power losses based on 5-degrees-of-freedom (DOF) operation is presented. In addition, several optimized 5-DOF modulation schemes are proposed, targeting different design optimization objectives e.g., zero-voltage-switching (ZVS) operation and converter power loss minimization.
A new isolated three-port DC-DC converter with a reduced number of active devices is also proposed in this thesis. The proposed converter is based on a hybrid dual-active-bridge (DAB) and phase-shifted full-bridge (PSFB) topology and it is able to achieve independent charging of HV and LV batteries using a new 3-DOF modulation scheme, while all of the semiconductor devices of the proposed converter operate with ZVS over a wide HV and LV battery voltage range.
Finally, a comparison of the TAB and the new hybrid DAB-PSFB converter is performed in terms of efficiency, volume and component count. Moreover, the comparison includes the non-integrated counterparts of each converter topology, considering the conventional architecture of separate OBC and APM converters. Results from the experimental testing of the converters are utilized along with finite-element (FE) simulation results to evaluate the performance of each converter topology and validate their effectiveness for future integrated on-board charger application
Model updating frameworks for the estimation of lateral soil-pile interaction parameters
Full text linkResilient infrastructure systems, particularly in safety-critical applications such as offshore wind turbines (OWTs), demand advanced monitoring frameworks that can accommodate complex dynamics and inherent uncertainties. Structural Health Monitoring (SHM) is central to this goal, ensuring the operational integrity of OWT foundations while supporting safety, efficiency, and sustainability. This thesis advances the field of SHM by integrating physics-based modelling with data-driven techniques, combining the reliability of numerical simulations and the adaptability of data-oriented methods. This hybrid approach overcomes the limitations of purely data-driven methods, which can produce accurate but physically inconsistent predictions, and purely physics-based models, which can be computationally expensive and sensitive to parameter uncertainties.
Focusing on soil-pile interaction (SPI), this work addresses key challenges in estimating critical system parameters that influence the dynamic response and structural integrity of pile foundations. The thesis develops and evaluates deterministic and stochastic model updating frameworks, each designed to handle varying data availability and changing environmental or operational conditions. The deterministic framework employs frequency-response functions (FRFs) using input-output data, while the stochastic frameworks utilise output-only data and Modal Assurance Criterion (MAC)-based updating. These frameworks are validated using numerical simulations, with field tests conducted in selected scenarios.
Throughout the thesis, numerous challenges are systematically addressed. These include achieving both physical interpretability and computational feasibility, maintaining accuracy under measurement uncertainties, ensuring robustness against varying operational conditions, and promoting scalability to real-world OWT systems. Addressing these challenges requires careful selection of an appropriate modelling approach, including model reduction strategies to balance accuracy and efficiency. The choice of parameters to be estimated, objective function formulation for robust performance, and selection or development of suitable optimisation algorithms are also critical factors. Additionally, the frameworks are designed to be applicable under operational conditions, where environmental and loading uncertainties must be accounted for.
This thesis demonstrates that hybrid SHM frameworks, integrating data-driven and physics-based methods, enhance the predictive accuracy and reliability of OWT foundation monitoring. The findings emphasise the role of vibration data in model updating for estimating operating parameters while reducing uncertainty. These frameworks offer a structured approach to quantifying uncertain parameters and assessing the condition of pile foundations under dynamic uncertainties. By bridging theoretical insights with practical frameworks, this research contributes to the advancement of SHM for pile foundations
Three essays on empirical corporate finance
No full textThis thesis contains three independent essays in empirical corporate finance with distinct perspectives. The first essay (Chapter 2) discusses the association between managerial ability and corporate financing decisions. Existing literature emphasizes the significant role of managers in capital structure management. Baseline results show that firms with high-ability managers strategically decrease the leverage ratio. This finding is robust after addressing endogeneity concerns and across alternative empirical specifications. The cross-sectional results suggest that the negative association between managerial ability and firm leverage is more pronounced when firms are less financially constrained, have lower uncertainties, make no attempt to meet or beat analyst’s earning expectations and with CEOs who have longer tenures. Additional analyses also find that skilled managers tend to lower the leverage adjustment speeds, show less (more) propensity on issuing debt (equity) and increase internal operating cash flows.
The second essay (Chapter 3) provides a new insight on how managerial compensation frictions, especially CEO tax burdens could impact corporate environmental performances. Recent studies demonstrate that managers with higher tax burdens are less likely to sell stocks, becoming overexposed to firm-specific risks, thereby significantly reducing their propensity to engage in risky corporate decisions and prompting a greater focus on firm stability over the long run. The findings indicate that firms decrease the generation of corporate toxic waste when CEOs’ tax burdens increase. This conclusion is valid across a range of identification tests as well as different robustness tests. Results from a series of cross-sectional analyses reveal that the negative relationship between CEO tax burdens and the corporate toxic waste generation is more pronounced in firms with stronger external requirements on environmental offences, fewer financial constraints, and for CEOs with limited hedging opportunities. Further analysis also shows that higher CEO tax burden contributes to better CSR engagements.
The third essay (Chapter 4) explores the determinants of corporate risk-taking by deploying machine learning. Using a boarder series of linear and nonlinear machine learning models, results find evidence that machine learning can significantly predict and select the efficient determinants of firm’s risk-taking, as well as the heterogeneities of risk appetites across sub-samples. Comparing all ML methods, the results indicate that extreme gradient boosting (XG-Boost) outperforms the other models in predicting corporate risk-takings as well as classifying their magnitudes. To interpret the predictive performance, the tree-based feature importance and SHapley Additive exPlanations (SHAP) plots indicate that firm-specific attribute more in explaining risk-taking behavior. Overall, this study contributes prior studies on firm risk-taking decisions by showing the outstanding predictive power of machine learning tools and providing novel insights for practitioners
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