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The impact of mood on children’s egocentrism
Get PDFBackground: Theory of mind (ToM) is the ability to attribute mental states to others. Egocentric bias occurs when one’s own knowledge interferes with the judgement of another’s mental state. Happy adults have been shown to exhibit increased egocentricity. This study extends this to children by investigating how happiness influences their degree of egocentric bias and contributes to understanding the underlying processes of ToM in children.
Methods: Eighty-seven children were exposed to either happy or neutral mood conditions and completed a continuous false belief task. Mood ratings were taken before and after manipulation.
Results: A mixed design ANOVA revealed a significant effect of false belief on bias, but the effect of mood on bias was not significant, and there was no significant difference in the interaction between belief type and mood condition. The lack of a successful mood manipulation explained these findings. A Spearman’s correlation between egocentric bias and mood scores after induction showed a moderate positive correlation.
Conclusions: The current study indicated higher self-reported happiness predicted increased egocentric bias in judgments, consistent with findings observed in adults. Overall, these results contribute to the two-step model of ToM, where happier children are more prone to interference from readily accessible defaults, whilst less happy children demonstrate more effortful ToM reasonin
Characterising the molecular interaction between CLEC14A and Multimerin 2
Get PDFThe C-type lectin domain group 14A (CLEC14A) protein, a single pass transmembrane spanning glycoprotein, is an endothelial expressed protein found to be highly and selectively expressed on tumour vessels. CLEC14A interacts with various ligands including the extracellular matrix protein Multimerin 2 (MMRN2) and heparan sulfate polysaccharides. CLEC14A’s interaction with MMRN2 elicits a proangiogenic phenotype and upon blocking this interaction there is a reduction in tube formation and cell migration in vitro and tumour size in vivo. The aim of this project was to further characterise the interactions of CLEC14A with MMRN2 and heparin as well as explore the structure of CLEC14A and MMRN2. To this end an alanine-scanning mutagenesis approach, coupled with AlphaFold predictive modelling, determined that residues S137, T139 and R141 of human CLEC14A directly interact with MMRN2. The R161 residue of CLEC14A was also shown to partially contribute to the interaction with heparin. It was revealed that the R100 and R141 residues of CLEC14A form part of the binding epitope for the CRT4 antibody which blocks the interaction between CLEC14A and MMRN2. The CRT4 antibody, known to modulate tumour vessel formation, also blocked the interaction between CLEC14A and heparin, thus expanding our understanding of how this reagent is acting to mediate its biological effects. Additionally, analytical ultracentrifugation revealed that MMRN2 forms a trimer in solution, providing new insights into how CLEC14A may bind to MMRN2. Taken together, the data presented in this thesis expands on the current understanding of the interaction between CLEC14A and MMRN2 and heparan sulfate, providing valuable strategies that could be used to better determine how different ligands affect the biology of CLEC14A. This may ultimately give rise to novel therapeutic strategies to target CLEC14A in cancer
Exploring Muslim university students’ experiences and identity construction within HEI settings
Get PDFThis thesis provides an in-depth exploration of their multifaceted experiences through the lens of the novel Muslim Identity Intersectional Matrix (MIIM) conceptual framework. Utilising a qualitative methodology which involves semi-structured interviews with 30 Muslim students aged 18-21 from two universities in the West Midlands region, this study captures the diversity and complexity of Muslim students' identities, challenges, and strategies within the university context. The key findings revealed the centrality of faith in participants' lived experiences, manifesting across a spectrum of interpretations and practices that are intricately woven into their identity construction processes. As Muslim students navigate university life, they undergo transformations to negotiate their religious, cultural, and academic identities in secular institutional environments. The findings also highlight pervasive experiences of marginalisation and Islamophobia, ranging from microaggressions to systemic exclusion, which undermine their sense of belonging on campus. Nonetheless, Muslim students demonstrate resilience and agency, actively resisting marginalisation through community building efforts, strategic self-representation, and embodied placemaking practices, carving out inclusive spaces that affirm their multifaceted identities. These contrasting university environments shape Muslim students' experiences, support, engagement, and academic aspirations, underscoring the significance of the institutional factors. The MIIM framework developed in this thesis offers a nuanced understanding of the complex processes involved in Muslim students’ identity formation and institutional engagement. By amplifying Muslim students' voices and perspectives, this study challenges deficit narratives and highlights their creativity and resourcefulness in navigating university life. These findings provide invaluable insights for policymakers, educators, and practitioners aiming to create truly inclusive and equitable environments that empower all students to thrive academically, socially, and spiritually, embracing religious pluralism as an integral part of the academic and social landscape
Investigating the potential use of highly sensitive tear and saliva analysis to enable non-invasive diagnosis, monitoring, and prognostication in multiple sclerosis
Get PDFMultiple sclerosis (MS) is a progressive neurodegenerative condition characterised by chronic immune-mediated demyelination and axon loss in the central nervous system, leading to progressive decline in motor function and disability. While advancements in treatments have significantly enhanced the longevity and quality of life of individuals living with the condition, timely and accurate diagnosis remains critical. Oligoclonal banding (OCB) and elevated Kappa and Lambda free light chains (FLCs) in cerebral spinal fluid (CSF) are hallmarks of MS. However, CSF sampling via a lumbar puncture is a highly invasive procedure, requires specialist training to perform and is often an unpleasant experience for patients. This study aimed to evaluate the feasibility of non-invasive tear and saliva analysis as alternative methods for the detection of OCB and FLCs.
A cohort of 40 healthy donors (HDs), 20 MS patients and 60 non-MS neurological condition controls (NCCs) undergoing lumbar puncture investigations were recruited to the study. Blood, saliva, tear fluid, and CSF (from lumbar puncture patients) were collected and analysed utilising highly sensitive immunoassays developed by the Clinical Immunology Service. Serum reference ranges for Kappa and Lambda FLCs were established by Optilite analysis, while saliva and tear FLCs were quantified by ELISA. IgG and total free and bound immunoglobulin OCB detection was performed on all sample types using isoelectric focussing (IEF).
Significantly reduced saliva and tear secretion was observed in both MS patients and NCCs compared with HDs. Notably, FLC quantitative parameters exhibited similar trends in MS patients and NCCs when compared to HDs. Kappa FLC secretion and Kappa: Lambda ratios were elevated in serum, decreased in saliva and unchanged in tear fluid when compared to healthy controls. OCB was absent in HDs and NCCs, but faint bands were present in 20% MS patients tears and 25% MS patient saliva.
The tear and saliva biomarkers examined in this study did not achieve sensitivity or specificity requirements to warrant an expansive follow-up study. However, the investigation provided useful insights into the collection and analysis of the sample types. Disparities in results between MS patients may mirror the heterogeneity of MS presentation and disease course, underlining the demand for further biomarker research. The ability to accurately stratify patients based on accurate biomarker profiles could transform clinical investigations for patients and clinicians, pave the way for personalised medicine and increase our understanding of the pathophysiology of the condition. Complementary studies could aim to explore the variability in results among MS patients, particularly regarding the presence of OCBs in tears and saliva. Also, the similarity of FLC parameters between MS patients and NCCs could be investigated through a more stringent cohort analysis of age, medication usage, sample collection times and co-morbiditie
Development of a novel Polyketone biomaterials platform from renewable resources
Get PDFCommodity plastics derived from petroleum sources are inherently non-degradable or minimally degradable which inevitably leads to the formation of microplastics or nanoplastics. The adverse consequences impact on the environment and human health. Over the past few years, renewable feedstocks, such as biomass, have become an alternative to petrol-derived feedstocks, thanks to their sustainability, abundance, and being environmentally friendly. Nonetheless, the manufacturing process still needs some non-degradable additives to enhance the mechanical properties and thermal stability of the polymer materials from renewable resources.
Polyketones (PKs) are generally an important family of thermoplastics, along with polyesters, polycarbonates, polyamides, polyurethanes, polyurethanes, and polyimides, that have been developed and manufactured to fulfill the needs of modern society for high-performance materials with excellent thermomechanical properties. Recently, polyketones have gained interest for some applications related to photo-triggered materials use. PKs are generally prepared via chain-growth metal-mediated polymerization which usually uses carbon monoxide and transition metals. In addition to the harm of monomer and catalyst used, this strategy also limits the structural complexity and range of thermomechanical properties of the resultant polyketones.
Conventional polyketones contain polyolefin backbones and behave like polyolefin in their photodegradation. They commonly degrade into a nonselective degradation pathway which is known as Norrish pathways. Therefore, a step-growth click polymerization is employed to address these challenges by inserting renewable and sustainable building blocks in their preparation. Manipulating the pendant group or main chain of the polymers enables structurally diverse polyketones and variable thermomechanical properties, yet their degradation can be controlled through well designed photocleavable linkage. The resulting polyketones (F-C6A and Poly(HMDA10-co-EDEA90) display comparable tensile strengths to PET and HDPE respectively (but having half of their elongation at break values) with high glass transition temperature values (amorphous behavior). In addition, they enable to degrade under controlled UV light via a novel photodegradation pathway
DNA-modified surfaces and frameworks for sensing and imaging applications
Get PDFNucleic acids act as biomarkers for a host of diseases and conditions. Various technologies,almost all employing some form of modified DNA, have been developed to sense extracellular nucleic acids. An important component of many nucleic acid biomarkers are single nucleotidevariants (SNVs). SNVs are positions in DNA in which a single nucleotide or base pair is altered,and include single nucleotide polymorphisms, point deletions, and epigenetic mutations. Some SNVs are directly or indirectly linked to certain diseases, and therefore their detection can offer valuable diagnostic and prognostic information. Currently, fluorescence-based methods are the dominant approaches used to sense or map SNVs. Whilst effective, their drawbacks include the need for careful experimental design to avoid false-positives, the inability to interrogate the nature of a mutation (i.e., to determine which other base is present), and their often complex and time-consuming nature. Electrochemical sensing of SNVs offers an alternative to fluorescence, with the potential for greater synchronisation with our increasingly digital, device-led world. The bulk of this thesis reports on the development of a surface-immobilised heterobimetallic DNA probe capable of electrochemically distinguishing between nucleobases at a single site (i.e., SNVs) in target DNA strands. Two redox-active complexes, a copper cyclidene macrocycle and a ferrocene unit, are incorporated into DNA using automated solid-phase synthesis. The copper cyclidene is incorporated internally and the ferrocene is appended to the 5′ end of the probe, with each producing a distinct electrochemical signal allowing for a ratiometric sensing approach. Key properties of the probe, including sensitivity, stability, and regeneration capability are determined. Clinically relevant SNV mutations associated with cancer and COVID-19 are detected using the bimetallic probe. Additionally, investigations into the SNV sensingmechanism of the copper cyclidene, efforts to improve the sensitivity of the probe, and the expansion of targets to include RNA biomarkers are described. Also included in this thesis is the functionalisation of metal-organic frameworks (MOFs) with fluorescently-modified DNA. MOFs are crystalline materials composed of metal ions or clusters connected through organic linkers, the different combinations of which allow for the tuning of a MOF’s properties. The functionalisation of two different MOFs with complementary fluorescently-modified DNA, and efforts to bind them together via DNA hybridisation to create a single material that combines the properties of each individual MOF, are described herein
Luminescence lifetime-based sensing solid interfaces for the determination of Perfluoroalkyl substances (PFAS)
Get PDFThe presence of per- and polyfluoroalkyl substances (PFAS) in humans arises from their large-scale use in multiple industrial and consumer applications. Such uses have led to human exposure via a range of pathways of which is concerning given evidence of the adverse health impacts of PFAS. However, conventional LC-MS methods for measuring PFAS are economically and logistically unsuited to monitoring compliance with this limit, and less expensive, faster and user-friendly methods for the quantification of PFAS are urgently required. Luminescence lifetime is an attractive analytical method for detection due to its high sensitivity and stability, and there is great interest for the design of detection platforms for monitoring of PFAS concentrations in different environmental contents. Herein, three novel luminescence lifetime-based sensing platforms were developed for the accurate and rapid detection of PFAS (e.g. PFBA, PFOA, PFNA, PFDA, etc) in different environmental contexts.
Chapter III describes the fabrication and function of a novel and facile luminescence sensor for PFOA detection based on iridium modified gold surfaces. These surfaces were modified with lipophilic iridium complexes bearing alkyl chains, namely, IrC6 and IrC12, and Zonyl-FSA surfactant. Upon addition of PFOA, the modified surfaces IrC6-FSA@Au and IrC12-FSA@Au show the largest change in the red luminescence signal with changes of the luminescence lifetime that allow monitoring of PFOA concentrations in aqueous solutions. The platform was tested for measurement of PFOA in aqueous samples spiked with known concentrations of PFOA, and demonstrated capacity to determine PFOA at concentrations >100 µg/L (240 nM).
Chapter IV describes a functionalised gold surface based on a SAcbisDBM ligand and Europium(III) to rapidly and accurately measure the concentrations of C4 to C10 PFCA in waste fabrics. The surface was modified with SAcbisDBM ligand, subsequently coordinated with Europium(III), namely Eu-SAcbisDBM@Au surface, displaying high affinity towards perfluoroalkyl carboxylic acids (PFCA) and is reusable. Under optimal conditions, the surfaces can detect >80 nM PFCA. The potential utility of the sensor is demonstrated by the good agreement between concentrations recorded by the sensor and LC-MS measurements of C4-C10 PFCA in 34 leather, leatherette, and textile samples.
Chapter V investigates the use of near infrared-emitting lanthanides, such as Neodymium(III) and Ytterbium(III) coordinated with the SAcbisDBM ligand, in solution (Nd/Yb-SAcbisDBM) or on plasmonic gold (pAu) surface (Nd-pAu and Yb-pAu), to detect PFCA such as PFOA, PFNA, and PFDA in water. Upon the addition of PFCA (e.g. PFDA), both Nd-SAcbisDBM and Yb-SAcbisDBM show a significant increase in luminescence, displaying a detection range as low as 2 µM and 10 µM, respectively. The luminescence properties of Nd-pAu and Yb-pAu also present a positive correlation with the concentration of PFCA. The sensing systems exhibit enormous potential for the detection of PFAS, offering valuable insights for environmental monitoring
Algorithms and Software for Structured Semidefinite Optimization
Get PDFThe goal of this thesis is to find solutions to large-and-sparse linear Semidefinite Programs (SDPs) with low-rank solutions and/or low-rank data, and we introduce a new code for the solution of these problems. We are investigating an Interior-Point (IP) approach to solve these problems. A general bottleneck of IP methods is assembling the so-called Schur complement equation and finding a solution for it, in which the matrix becomes increasingly ill-conditioned as the interior-point method makes progress toward the solution. To tackle this challenge, instead of the direct solver (Cholesky factorization), we suggest using a Preconditioned Conjugate Gradient (PCG) method within an interior-point semidefinite program algorithm and introduces a novel and efficient preconditioner that fully utilizes the low-rank information. Efficient preconditioners allow PCG to converge to an approximate solution of the linear equation in a few iterations, independent of the ill-conditioning of the Schur complement matrix. The efficiency is demonstrated by numerical experiments using the truss topology optimization problems of growing dimension which is formulated as large-scale SDP with the low-rank solution and the sensor network localization problems. The numerical re-sults demonstrate that our preconditioner is working better than preconditioners recently proposed by Zhang and Lavaei, based on a similar idea. Also, our Matlab implementation outperforms MOSEK and other available IP-based software. Furthermore, we use this IP approach to solve linear SDPs arising from higher-order Lasserre relaxations of Unconstrained Binary Quadratic optimization Problems (UBQPs). For these problems, the preconditioner makes use of the low-rank structure of the solution of the relaxations. Thus, we re-write the moment relaxations and use an l1-penalty approach within the IP solver to deal with the arising linear equality constraints.
The efficiency of this approach is demonstrated by numerical experiments with the MAXCUT and other randomly generated problems and a comparison with a state-of-the-art semidefinite solver and the ADMM method. As a by-product, we observe that the second-order relaxation is often high enough to deliver a globally optimal solution of the original problem.
In addition to this study, we look at how Polynomial Optimization techniques can be applied to Geometric Modeling problems. We discuss some examples of geometric modeling problems, and how they can be solved utilizing polynomial optimization tools. At the end, we report and analyze some experimental findings
Developing a sustainable water resources management assessment framework (SWRM-AF) for arid and semi-arid regions
Get PDFThe rapidly growing world population highlights the need for evaluation methods like indicator-based water sustainability frameworks (IBWSFs) to assess and improve water resources management (WRM) practices. This is particularly important in arid and semi-arid regions (ASAR) where water resources are scarce. Furthermore, a particular IBWSF that fully fits the context of ASAR could not be found in the literature. Therefore, a sustainable water resource management assessment framework (SWRM-AF) has been developed, specifically tailored to evaluate water use in the domestic sector of countries with similar water conditions to those of the Gulf Cooperation Council (GCC) countries.
The first step in the process of developing the SWRM-AF is to create a conceptual SWRM-AF, which consists of four components (i.e., three pillars of sustainability: environment, economy, and society plus infrastructure) underpinned with 24 selected indicators. These indicators were chosen rigorously through an extensive literature review. Each indicator is provided with a brief description and justification. One contribution of this research is that, for the first time, every indicator is presented with clear and straightforward instructions represented by coloured-code tables to explain how to evaluate each. In addition, social indicators such as the ‘intervention acceptability’ and environmental indicators to tackle the impact of the desalination treatment plants have been included to form a more holistic framework applicable to GCC countries.
The second step is to utilise the Delphi technique as a participatory method to refine and validate the conceptual framework. This technique employs an iterative questionnaire to achieve consensus, through which 60 expert stakeholders from the GCC countries were invited to assess each indicator across four components and assign their respective weights. This process, through two rounds, resulted in a final version of SWRM-AF consisting of 4 equal-weight components and 17 indicators. Also, it was found that indicators within the social, economic, and infrastructure components should carry equal weights, while indicators within the environmental component should be assigned different weights.
Lastly, data about the water sector of the Kingdom of Saudi Arabia (KSA), which was selected as an example of GCC countries, were collected to give a comprehensive idea about the overall water situation. Then, an application of the final SWRM-AF to the WRM of the domestic sector of the KSA, focusing on its current practices and assumptions of possible future scenarios, is presented
Cyber-physical merged learning for online optimisation of multi-mode hybrid vehicles with diverse time-scale objectives
Get PDFA comprehensive investigation of the energy management and optimisation techniques used in multi-mode plug-in hybrid electric vehicles (PHEVs) is presented in this thesis. It focuses on using artificial intelligence and sophisticated control algorithms to improve multi-mode PHEV performance and efficiency. With the goal of increasing fuel efficiency and product life cycle, the research combines cutting-edge techniques for cyber-physical adaptive control schemes, real-time energy management, and battery state estimation.
This thesis first presents the development of a dedicated adaptive particle swarm optimisation (DAPSO) for offline optimisation based on a digital twin boost of the efficiency and dependability of PHEVs’ energy management system (EMS) control. In terms of fuel efficiency and battery state-of-charge (SoC) maintenance, the DAPSO is superior in performance compared to traditional algorithms.
Then, regarding the electrification of multi-mode PHEVs, an intelligent digital model of a battery is developed with challenging circumstances for an automotive battery to obtain real-time status estimation. In order to improve functionality and reliability in real-time applications, this model uses both deep neural networks (NN) and Gaussian process regression with automatic relevance determination (ARD-GPR) approaches based on a modified equivalent circuit battery model (ECM) for handling health indicators throughout the charging and discharging processes.
This thesis finally develops a cuboid equivalent consumption minimisation strategy (CECMS) for multi-mode PHEVs. The C-ECMS provides improved performance in online optimal energy management with multiple objectives in diverse time scales. In real-world driving conditions, this strategy improves overall performance and economy by establishing a compromise between battery health, fuel efficiency, and SoC control accuracy.
The results address both the scientific and practical elements of automotive technology, providing insightful information for the development of more efficient and environmentally friendly multi-mode PHEVs
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