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Exploring how accounting firms build dynamic capabilities in Artificial Intelligence-driven Analytics (AIDA) as they pursue digital transformation
Get PDFThis thesis investigates how accounting firms develop dynamic capabilities (DCs) in Artificial Intelligence-driven Analytics (AIDA) whilst pursuing digital transformation. Through qualitative multiple case studies involving 24 participants from 11 accounting firms across different size categories in Singapore—including Big 4s, Mid-tiers, and Boutiques—the research examines the processes through which accounting firms sense opportunities for AIDA adoption, seize these opportunities through strategic investments, and transform to effectively integrate these technologies.
By using the DCs framework as the main theoretical lens, supplemented by strategy-as practice (SAP) and technologies-in-practice (TIP) perspectives, the study identifies distinct patterns in how accounting firms of different sizes build capabilities for AIDA adoption. The findings reveal that while accounting firms share common objectives of enhancing client service delivery, their approaches to developing DCs vary based on firm type, market position, and strategic priorities. Big 4s prioritise global integration with local flexibility, Mid-tiers focus on operational efficiency within resource constraints going with pragmatic and workflow-specific implementations, and Boutiques stay agile and emphasise client-specific customisation to specialise in niche areas
Development of a novel viral vector-based mouse model for Lewy Body dementia
No full textAbstract not currently available
The influence of environments on energy transfer
Get PDFEnergy transfer between atoms/molecules, one of the most basic interactions within atomic and molecular systems, is important in many diverse areas of science. The ability to control these processes is therefore a powerful tool with applications in various fields, and one method to achieve this influence is through the use of macroscopic bodies. Making use of the theoretical framework of macroscopic quantum electrodynamics (QED), the environment of a microscopic system can be introduced into the quantum description, and its influence on intermolecular energy transfer can be characterized. In this work, we explore the ways in which intermolecular interactions can be impacted by a macroscopic environment. We derive a general expression for the rate of resonant energy transfer (RET) between a donor and an acceptor in an arbitrary, reciprocal environment and examine how the medium’s properties and the molecular positions affect the interaction rate. Our consideration is then extended to include non-reciprocal media, again calculating a general expression for the energy transfer rate and applying to a simple setup containing non-reciprocal media. In particular, we investigate how the properties of the medium can be altered to promote unidirectional energy propagation. We will also explore an application of this principle, which makes use of inverse design in the creation of an optical isolator. In real-world situations, a donor and acceptor can also be coupled to additional interacting bodies as well as their environment, and these can have an intricate impact on the rate of energy transfer between them. The introduction of a third molecule significantly complicates the calculation of the rate, so in this work we use canonical transformations to reduce this computational complexity and derive a general expression for the rate of three-body RET in a macroscopic background. Applying this to some simple setups demonstrates the distinctive effect the mediating body can have. Finally, we investigate how a macroscopic body can be used to induce a superabsorbing state in a system of dipoles via control of the intermolecular coupling. After a demonstration of this principle for a simple model system, we consider a ring of optical dipoles, inspired by naturally occurring photosynthetic systems. We demonstrate how the placement of a macroscopic sphere inside the ring can produce superabsorption in the system, making it suitable for use in artificial light harvesting and showing performance superior to previous methods
Zirconium-based metal-organic frameworks for cancer therapy via multi-surface modifications
No full textAbstract not currently available
Caste and digital: a study on the reproduction of educational inequalities in the era of technology enabled learning in Kerala, India
Get PDFThis research is specifically targeted at understanding the disparity in the personal use of technology for education among higher secondary students in India, as these are the most competitive years in Indian schooling (Mann et al., 2021). Employing a digital sociological framework, this study particularly explored the role of the caste system, a religiously endorsed social hierarchy, on students' access to, usage of, and attitudes towards digital technology in the context of education.
Semi-structured interviews were applied to collect data from 45 higher secondary students hailing from three different caste groups and four distinct categories of schools in the state of Kerala, India. Kerala was an important sociopolitical and cultural setting for this inquiry. The relationship between caste and digital in the socially, educationally (Singh, 2011), and digitally (Moinuddin, 2019) most progressed region in the country provided important insights.
This research is based on Bourdieu’s concepts of capital and habitus, contextualised within the digital milieu, featuring the concepts of digital capital and digital habitus. By intertwining these notions with the caste structure, this study identifies the intricate relationship between capital, habitus, and caste in the digital domain. Through this conceptual lens, the researcher elucidates how the caste backgrounds of students impact their interaction with technology, thereby contributing to the reproduction and intensification of disparity in economic, social, and cultural capital in the digital domain, coupled with the distinction in digital habitus between different caste groups.
The difference in access to material and non-material digital resources, digital skills and usage, and the motivation to use technology for building the future, between different caste groups were discovered. This research not only revealed the digital-educational inequalities but also identified the reasons for its perpetuation. The study recognises the influence exerted by pre-existing sociocultural, economic, and technological factors including caste, family, neighbourhood, schools, and digital spaces in reinforcing the digital and educational inequalities. Furthermore, research widened the scope of Indian digital sociological research and policymaking by reconceptualising digital inequality, digital capital, and digital habitus in Indian context
Estimation of the independent causal effect of T2DM on cancer incidence
Get PDFBackground:
Diabetes mellitus (DM) is a chronic metabolic disease whose prevalence has risen dramatically over the past two decades, increasing from 108 million cases in 1980 to 537 million in 2021, with projections estimating 783 million cases by 2045 (International Diabetes Federation, 2021). Type 2 diabetes mellitus (T2DM) is the most prevalent form, accounting for over 90% of cases globally. In addition to its micro and macrovascular complications, emerging evidence links T2DM to an elevated cancer risk. While the association between T2DM and cancer has been widely studied, no causally interpretable meta-analyses have been published on the relationship between T2DM and cancer risk across a range of cancer types.
Aim:
This thesis aims to assess the independent causal effect of T2DM on cancer risk across
multiple cancer types. In this context, independent causal effect refers to a relationship that is not influenced by confounding factors.
Methods:
A comprehensive and updated systematic review (SR) was conducted to identify evidence on the association between T2DM and cancer risk across various cancer types. Directed Acyclic Graphs (DAGs) were used to identify the minimum sufficient adjustment set (MSAS) to control for confounders. Studies that accounted for the MSAS in their adjusted analyses were included in the adjusted (causal effect) meta-analyses, which used the DerSimonian and Laird inverse variance method for random-effects models to synthesize data from multiple studies. Subgroup analyses were performed by sex, race, study design, menopausal status (for breast cancer), time since T2DM diagnosis, and antidiabetic drug classes. Additionally, unadjusted (association) meta-analyses were conducted to examine the relationship between T2DM and cancer risk, with corresponding subgroup analyses. Statistical heterogeneity was assessed using the I² statistic, and potential publication bias was examined through funnel plot inspection and Egger’s test. A burden of disease analysis was also conducted to estimate the cancer burden due to T2DM for the cancer types found to be causally associated with T2DM in the meta-analyses.
Findings:
A total of 18,086 publications were screened, and 250 studies were included in the SR, covering 30 countries and 63 cancer types. Of these, at least one effect estimate meeting the MSAS criteria was reported for 31 types. Meta-analyses for 17 cancer types revealed statistically significant causal associations for breast (relative risk [RR] 1.11; 95% confidence interval [CI]: 1.04–1.18), colon (RR 1.30; 95% CI: 1.12–1.50), endometrial (RR 1.94; 95% CI: 1.43–2.63), kidney (RR 1.67; 95% CI: 1.40–1.98), pancreatic (RR 1.73; 95% CI: 1.46–2.05), and prostate cancers (RR 0.81; 95% CI: 0.72–0.91). Subgroup analyses showed no statistically significant differences in cancer risk by sex, geographic region (proxy for race), or study design. For breast cancer, the risk due to T2DM was comparable in premenopausal and postmenopausal women. In the global burden analysis, 2% of cancer cases (105,084 cases) in 2025 are expected to be attributable to T2DM prevalence in 2021 for the cancer types found to be causally associated with T2DM. Endometrial cancer will have the highest burden, with 1 in 20 cases (24,072) attributable to T2DM, followed by pancreatic cancer, with 1 in 25 cases (23,530). Pancreatic cancer is also projected to account for the highest disability-adjusted life years (DALY) and economic burden (INT $21,844.70 million). Regionally, the Middle East and North Africa is projected to experience the highest burden (2.8%), while Africa will have the lowest (0.7%).
Conclusion:
This thesis identifies specific cancer types for which causality with T2DM is interpretable. Recognizing these causally interpretable associations can inform the development of more targeted public health interventions, particularly in cancer screening and prevention strategies for individuals with T2DM
In the face of diversity: revealing the influence of ethnicity and culture on social trait face perception
Get PDFOn a daily basis, people make spontaneous judgements about who to trust or avoid based on facial appearance. Because of their considerable downstream consequences, a longstanding goal has been to understand which facial features drive social trait judgements. Despite emerging evidence showing that ethnic and cultural diversity influence social trait perception, most knowledge remains centred on White Western observers perceiving White faces. This bias questions the generalizability of prominent theories and feature-based models. In this thesis, I combine a data-driven reverse correlation approach with a generative model of 3D human faces to model the specific facial features of 3D shape and 2D complexion that drive perceptions of trustworthiness and dominance from three face ethnicities—Black African, East Asian, and White European—in two observer cultures—White Western and East Asian. Using information-theoretic analyses, I show that both White Western and East Asian observers perceive trustworthiness and dominance from a core set of facial features which are shared across face ethnicities, and map onto previous findings, plus novel face ethnicity-specific variations. These variations challenge the generalizability of prominent feature-based models and characterize the causal influence of face ethnicity on social trait perception. Further, while conceptually similar, the results for White Western and East Asian observers comprise different facial features. To formally test these differences, I next examine the cultural specificity of the modelled facial features across face ethnicities. Results show that, while White Western and East Asian observers provide similar social trait ratings for each face ethnicity, the features they base their ratings on differ. This questions previous claims of universality based only on rating comparisons. Further analyses reveal that the facial features specific to Western culture resemble specific emotion cues (e.g., smiling, frowning), whereas those specific to East Asian culture do not. This contrasts prominent theories such as emotion overgeneralization and highlights the Western-centric bias of current knowledge. Finally, I use a machine-learning approach and information-theoretic analyses to examine how face ethnicity, observer culture, and their synergistic interaction causally influence social trait perception. Results show that, across face ethnicities and observer cultures, social trait perception is driven by four feature sets: those that are shared, those that are face ethnicity-specific, those that are culture-specific, and those that are synergistic. Subsequent examinations of these feature sets confirm that they represent key sources of variance in social trait perception. These findings extend current efforts to quantify the relative contributions of the face, the observer, and their interaction and offer direct empirical support for modern theories of social trait perception. Together, this thesis responds to mounting calls to diversify psychological science by showing that ethnic and cultural diversity systematically alter the causal facial features for perception of key social traits, with direct implications for current knowledge and theory development
Epistemic injustice and the bias behind belief: feminist reflections on testimonial harm, conceptual engineering, misogyny and reproductive rights
Get PDFThe thesis conducts an in-depth examination of various aspects of epistemic injustice, focusing on how social structures, gender norms, and institutional power dynamics influence the production, distribution, and reception of knowledge. The discussion begins with a look at epistemic injustice, referencing the foundational work of Miranda Fricker to illustrate its impact on our lived realities. It specifically addresses certain domains of human knowledge and highlights the damaging manifestations of epistemic injustice. After establishing this basis, the thesis explores numerous facets of existence affected by epistemic injustice, including testimony, gender roles, gender conceptualisation, and the moral aspects of abortion, alongside the misogynistic ideals associated with specific social classes. A critical analysis of epistemic injustice reveals the current situation and uncovers structural domination by those in power, highlighting how individuals’ social positions perpetuate this dominance. The primary objective is to advocate for a liberation-oriented epistemology that aims to incorporate marginalised voices, challenge conventional definitions of knowledge, underscore diverse experiences, and transform epistemic practices to achieve equity. It weaves together theoretical insights from various fields to argue for reorienting epistemology to combat oppression and cultivate more inclusive and equitable knowledge systems
The dynamics of nitinol Langevin ultrasonic transducers
Get PDFLangevin ultrasonic transducers, especially sandwiched-type piezoelectric devices, are essential in industry and medicine for applications like ultrasonic welding and surgery due to their high power capability and design flexibility. This research focuses on adaptive Langevin transducers that enable multiple operating frequencies and tuneable resonances, responding to various operational environments. By integrating shape memory alloys, particularly nickel-titanium, Nitinol, these transducers can achieve continuous resonance tuning with temperature changes, distinguishing them from traditional multi-frequency designs.
The first section details the design, manufacturing, and characterisation of conventional Langevin transducers, introducing the incorporation of Nitinol into their structure. Mathematical models were built using one-dimensional (1D) and three-dimensional (3D) constitutive equations in piezoelectricity to simulate Nitinol transducer behaviours. While the 1D model offers advantages in computational efficiency and does not require complete material properties in 3D space, transducer dimensions and modes limit its accuracy. Following the simulations, this chapter outlines the considerations for integrating Nitinol into Langevin configurations while building on established methodologies for conventional transducers.
A core focus of this thesis is the practical fabrication of Nitinol Langevin transducers and their tuneable dynamics. Prototypes were developed incorporating various transducer configurations. Characterisations validated the tuneable resonances derived from Nitinol’s phase transformation, revealing two dynamics: active modal coupling and stable resonance. Notably, resonance stability under self-heating conditions was linked to the temperature-dependent properties of Nitinol’s austenitic phase. These dynamics are influenced by the device geometry, martensitic transformation of Nitinol, self-heating within the piezoelectric elements and their temperature dependent material properties.
In the final section, a case study on acoustic levitation using the Nitinol Langevin transducer is presented, aligned with the cascaded Nitinol configuration detailed in earlier in the thesis. The hypothesis is that by implementing a stable resonance condition under self-heating, a stable acoustic field can be generated. The results demonstrated that the stability in resonant frequency influences position, evaporation rate, and levitation time for water, acetone and isopropyl alcohol droplets, compared to a Langevin transducer in similar dimensions and made from conventional metals
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