VictorJuiz/thesis huggingface dataset:
Corporate Governance, Corporate Culture, and Innovation
Keywords: corporate culture
corporate governance
innovation
knowledge economy
neo-institutional theory
shareholder primacy

Mainstream corporate theory posits the standard shareholder-centered model (“SSM”) as the global normative standard for corporate governance and predicts convergence around a universalistic set of core principles and best practices, regardless of industry context; this thesis develops “knowledge primacy” as a production and knowledge-based critique of SSM. Knowledge primacy suggests optimal allocation of control in a firm’s governance structure is contingent upon, and an endogenous response to, the nature of its production process; it reviews empirical evidence and develops theory to support its hypothesis of an optimally inverse relationship between shareholder rights and the complexity of a firm’s production process, arising from: (i) problems of evaluation and control, and non-contractibility that increase with the knowledge formation, trust, and social exchange requirements of complex, knowledge-based production; and (ii) the tradeoff between lower agency costs and higher governance or “principal costs” associated with the allocation of control under conditions of “knowledge inversion” to cognitively unqualified public shareholders, resulting in net losses from the separation of knowledge and control. In certain production contexts, SSM is destructive of shareholder value, firm value, and social welfare. It rests upon a set of fundamentally ideological assumptions and assertions incongruent with the underlying logic, structure, and historical evolution of corporate law, which has accommodated the needs of increasingly complex production by shrinking the bundle of property rights associated with share ownership, thereby preserving optimal integration of knowledge and control. A neo-institutional perspective on organizations suggests that vestigial formal governance structures, such as shareholder meetings and shareholder votes, are institutionalized myths and ceremonies, retained and enacted as societally legitimated rationalized elements to provide cover for the decoupling of formal and informal controls required by complex production; the formal role of shareholders in the legal-rational structure of corporate governance may be largely symbolic, analogous to that of the Crown in the civic institutions of a constitutional monarchy such as Canada, or the “peppercorn” theory of consideration in the law of contract. The disruptive general implications of such a view for SSM are explored herein; knowledge primacy is compared and contrasted with director primacy and team production critiques of SSM.
The Role of Automaticity in the Cognitive Control of Human Action - A Magnetoencephalographic Study
Keywords: executive function
inhibition
magnetoencephalography
motor control
oscillations
pupil

Prominent theories on human action control propose two parallel brain processes: one fast and automatic, the other slow and deliberative. The slow, conscious processes are thought to be mediated by frontal theta (4-8 Hz) oscillations. One theory suggests that theta acts as an alarm signaling the need for control, and that frontal areas simply maintain action goals, without sensitivity to behavioural differences for achieving those goals. In order to test these hypotheses of frontal theta and executive function, three experiments were conducted. First, to examine the sensitivity of theta to behavioural differences in goal-directed actions, we compared magnetoencephalographic (MEG) recordings of theta activity in twelve healthy adults during two similar tasks: Go/No-Go and Go/Switch, requiring global and selective inhibition, respectively. We observed no differences between these two types of inhibitory control, but did observe differences during error responses. We hypothesized that error-related theta differences may have reflected covert differences in cognitive requirements between the two types of inhibition. Based on these results, a second study was designed to modulate cognitive requirements using the well-defined measure of cognitive effort, pupil diameter (PD), in twelve healthy adults. We developed a novel task combining implicit stimulus pattern learning with a Go/Switch task. The results demonstrated that subjects quickly learned the pattern without conscious awareness. Furthermore, a distinction between PD and behaviour was observed, highlighting the limitations of behavioural measures alone in capturing cognitive processes during task performance. Finally, in order to quantify theta during modulations in cognitive control, the third experiment was conducted on sixteen healthy adults performing the implicit Go/Switch task during MEG and PD recordings. Theta modulations were strongly correlated (r = 0.91) with PD, and therefore inferred to reflect cognitive effort. Furthermore, theta demonstrated a relationship with signals in the sensorimotor cortex. These results suggest a functional role for frontal theta oscillations in cognitive processes, including sensitivity to cognitive load but not behavioural differences while coordinating responses within the sensorimotor cortex. Furthermore, increased theta during implicitly learned unconscious responding demonstrated that conscious awareness was not required for cognitive effort. These results are discussed with respect to theories of action control.
Adaptive Techniques in Practical Quantum Key Distribution
Keywords: Free-space QKD
Machine Learning
Quantum Communication
Quantum Cryptography
Quantum Key Distribution
Quantum Network

Quantum Key Distribution (QKD) can provide information-theoretically secure communications and is a strong candidate for the next generation of cryptography. However, in practice, the performance of QKD is limited by "practical imperfections" in realistic sources, channels, and detectors (such as multi-photon components or imperfect encoding from the sources, losses and misalignment in the channels, or dark counts in detectors). Addressing such practical imperfections is a crucial part of implementing QKD protocols with good performance in reality. There are two highly important future directions for QKD: (1) QKD over free space, which can allow secure communications between mobile platforms such as handheld systems, drones, planes, and even satellites, and (2) fibre-based QKD networks, which can simultaneously provide QKD service to numerous users at arbitrary locations. These directions are both highly promising, but so far they are limited by practical imperfections in the channels and devices, which pose huge challenges and limit their performance. In this thesis, we develop adaptive techniques with innovative protocol and algorithm design, as well as novel techniques such as machine learning, to address some of these key challenges, including (a) atmospheric turbulence in channels for free-space QKD, (b) asymmetric losses in channels for QKD network, and (c) efficient parameter optimization in real time, which is important for both free-space QKD and QKD networks. We believe that this work will pave the way to important implementations of free-space QKD and fibre-based QKD networks in the future.
Role of Tafazzin in Hematopoiesis and Leukemogenesis
Keywords: acute myeloid leukemia
cancer differentiation
cardiolipin
leukemia initiating cell
mitochondria
tafazzin

Tafazzin (TAZ) is a mitochondrial transacylase that remodels the mitochondrial cardiolipin into its mature form. Through a CRISPR screen, we identified TAZ as necessary for the growth and viability of acute myeloid leukemia (AML) cells. Genetic inhibition of TAZ reduced stemness and increased differentiation of AML cells both in vitro and in vivo. In contrast, knockdown of TAZ did not impair normal hematopoiesis under basal conditions. Mechanistically, inhibition of TAZ decreased levels of cardiolipin but also altered global levels of intracellular phospholipids, including phosphatidylserine, which controlled AML stemness and differentiation by modulating toll-like receptor (TLR) signaling (Seneviratne et al., 2019).
Estimation of Hepatitis C Prognosis to Inform Treatment Prioritization Decisions
Keywords: Decision analysis
Hepatitis C
Markov model
Meta-analysis
Prognosis
Systematic review

Chronic hepatitis C (CHC) is a leading cause of hepatic fibrosis and cirrhosis. Fortunately, treatment has been revolutionized by the recently introduced direct-acting antivirals (DAAs). However, prompt access to DAA therapy remains a challenge owing to exorbitant drug costs, as well as other health system constraints. Given that HCV disease progression is highly variable, delaying curative treatment could have varying levels of health impact for different CHC subpopulations. To address these issues, the three studies presented in this thesis aim to 1) derive updated estimates of the natural history of HCV, 2) explore the variability in disease progression, and 3) use these prognostic estimates to help inform decisions on the prioritization of highly effective but costly DAA therapy. The first study derived updated estimates of HCV-related liver disease progression (i.e., FPRs, or fibrosis progression rates) through a systematic review and meta-analysis of the current literature evaluating hepatic fibrosis in treatment-naive individuals with CHC; and explored sources of heterogeneity. Stratified analysis revealed substantial heterogeneity across study populations. The second study complemented the biopsy-based estimates of HCV disease progression derived in the first study by generating alternative estimates of prognosis (i.e., LSPR or liver stiffness progression rates) based on a newer non-invasive assessment of liver disease through a systematic review and meta-analysis of the literature on transient elastography (TE)-based assessment of hepatic fibrosis in treatment-naive individuals with CHC. The study suggested that non-invasive prognosis of HCV is consistent with FPRs in predicting time-to-cirrhosis. However, the current literature was limited and more longitudinal studies of liver stiffness are needed to obtain refined estimates. The third study employed detailed information on HCV prognosis obtained from meta-regression models derived from the first study to help inform treatment prioritization decisions by quantifying the health impact (i.e., life expectancy and quality-adjusted life expectancy) associated with delaying DAA therapy for various CHC subgroups using decision-analytic methods. Taken together these studies present detailed prognostic information for various subpopulations of patients. The data presented in these studies should be a valuable resource for patients, clinicians, and clinical policymakers in the DAA era.
Bayesian Growth Mixture Model for Clustering Longitudinal Data
Keywords: Bayesian Analysis
Clustering
Growth Mixture Model
Longitudinal data
Non-linear Growth Trajectory
Variable selection

Studies of growth patterns of longitudinal characteristics are vitally important to improve our understanding of the development course of diseases. In these studies, it is often of great interest to cluster individual trajectories based on repeated measurements collected over time. Non-linear growth trajectories are often seen in practice, and individual data can also be measured sparsely at irregular time points, which may complicate the modeling process. This thesis begins with proposing a shape invariant growth mixture model for better clustering growth trajectory data with these features (Chapter 3). In the proposed model, non-linear patterns are captured by cluster-specific cubic B-spline smoothing functions within a latent class mixed effect model framework, and random effects reflecting the size, timing and intensity of the individual growth trajectories are modeled within each cluster to account for variation that is not explained by latent classes. We also compare our model to the commonly used standard growth mixture model and functional clustering approach. To better understand the clinical implication of different growth patterns, interests are usually not limited to which individuals belong to which subgroup, but also what factors are associated with individuals' class membership. This information could help clinicians provide early intervention to prevent the development of abnormal trajectories and therefore the development of diseases. Despite its importance in facilitating medical findings, little work has been done in selecting the predictors related to class membership in the context of growth mixture models. Therefore, we aim to extend the shape invariant mixture model we proposed to a unified Bayesian growth mixture model to allow incorporating covariates. To achieve this objective, in Chapter 4 we first review the currently available Bayesian variable selection approaches and compare their performance in terms of variable selection and prediction. And in Chapter 5, we propose a unified growth mixture model allowing for simultaneously clustering growth trajectories and selecting important covariates that are associated with the class membership. Bayesian inference via Markov chain Monte Carlo (MCMC) algorithm is implemented to estimate the parameters of interest. Results from analyzing real and simulated data are presented and discussed throughout this thesis.
The Feasibility and Usefulness of Applying a Health Economic Framework to Prioritize Quality Indicators: A Demonstration with Chronic Obstructive Pulmonary Disease
Keywords: chronic obstructive pulmonary disease
health economics
quality indicators

The modern quality movement has placed increased attention on health care performance. As a result, quality indicators, which are quantitative measurements of health care performance, have become increasingly prevalent in health care systems. Although many health systems define improving population health and reducing health care costs as priorities, many quality indicators are selected using criteria that do not always align with these priorities. Health economics offers a framework for explicitly bringing considerations of population health and health care costs into the process of prioritizing quality indicators. This research sought to demonstrate the feasibility of operationalizing the health economic framework to prioritize quality indicators and explore the usefulness of this method. Quality indicators for smoking cessation and oxygen therapy in chronic obstructive pulmonary disease were used as examples to demonstrate the feasibility of associating variations in indicator values with variations in quality-adjusted life years (QALYs) and costs. The joint variation in QALYs and costs was represented as incremental net health benefit (INHB), which represents the QALYs gained less its opportunity cost. The first two studies demonstrated how quality indicators could be ranked by their relationships to QALYs and costs. However, uncertainty in the values of candidate indicators could affect how quality indicators are prioritized. Linear meta-models offer a method that is partially successful in prioritizing indicators in the presence of uncertain indicator levels. Focus groups, with participants representative of stakeholders who would select or use quality indicators, were conducted to explore their perceived usefulness of prioritizing quality indicators under a health economic framework. The usefulness and applicability of the framework appeared to revolve around three main themes of incorporation of evidence, ease of understanding or interpretation of health economic outputs, and the scope of the framework. Ease of interpretation appeared to be the main barrier to the utility of the health economic framework in prioritizing quality indicators. Collectively, these studies show how a health economic framework can be operationalized to prioritize quality indicators in a way that is potentially useful, but resource requirements and barriers in interpretation of the health economic framework may limit its adoption.
Invasion in the Light of Evolution: An Integrative Approach Using Two Widespread Widow Spider Species
Keywords: behaviour
dispersal
invasive species
local adaptation
physiology
plasticity

As invasive species spread around the world, understanding the factors underlying invasion success has become increasingly important. Using an evolutionary perspective to examine biological invasions, I investigated how organisms are able to rapidly adapt to new environments, and how selection on phenotypic traits changed over time during sequential stages of the invasion process. In this thesis, I used lab and field studies to assess the importance of behaviour, physiology, morphology, and plasticity to widow spider invasion success. Using this variation in invasion history, I explored patterns across organismal, population, and species-level scales. In Chapter Two, investigated the effects of metabolic rate on behaviour in Australian redback spiders, Latrodectus hasselti, and links between behavioural variation and fitness components measured in the field and laboratory. My work showed that metabolic rate influences fitness via correlation with multiple behaviours, but that metabolic rate alone does not drive all individual behavioural differences. In Chapter Three, I tested preadaptation and local adaptation in a native and an invasive population of L. hasselti to investigate tolerance of novel environmental conditions experienced in the invasive range. In this chapter, I showed that invasive populations may be able to thrive in novel environmental conditions because of increased behavioural plasticity, tolerance of temperature fluctuations, and higher fecundity. In Chapter Four, I compared populations of L. hasselti that are native, established invasive, and newly invasive, and assessed the relative importance of phenotypic traits likely to predispose a species to invasion success. I found that invasive populations of Australian redback spiders diverged from the native Australian population in behaviour, life history, and morphology. In Chapter Five, I tested hypotheses of behaviourally mediated spatial sorting and changes in tradeoffs during invasive spread using two independent invasions of brown widow spiders. I found similar patterns of increased dispersal propensity in two independent invasions of brown widow populations in Israel and the United States. These common patterns suggest that dispersal ability under positive selection in invasive populations, particularly the recently established populations. I infer that behavioural plasticity and dispersal propensity, together with a preference for human-disturbed environments, may underlie invasion and establishment in invasive widow species. In sum, my thesis has expanded our knowledge of how evolutionary processes affect the spread of invasive species through local adaptation, selective filters in the invasion process, and spatial sorting.
A Foucauldian Discourse Analysis of Diabetes Knowledge Translation and the Governance of Family Physicians and Endocrinologists in Canada
Keywords: diabetes
discourse
governmentality
power
qualitative research
social sciences

Over the past thirty years, improving the health and lives of people with diabetes has been discussed from the perspective of diabetes knowledge translation: the process of implementing clinical practice guidelines into the care of as many people with diabetes (PWDs) as possible. While the majority of research has focused on discovering and implementing knowledge translation initiatives to overcome the problem of clinical inertia, there is less attention being awarded to what is actually happening in these well-intentioned practices. This thesis uses a critical social theoretical perspective from which to examine the ways in which we think and talk about good diabetes care shape the possibilities for physician scope of practice. The conceptual framework used to inform this study is built primarily from Michel Foucault’s concept of governmentality - a historically locatable way of thinking about how we “conduct the conduct” of ourselves and others to achieve specific goals through a variety of explicit and implicit practices, techniques, knowledge and power relations (Dean, 2010). More specifically, I examined the manner in which family physicians and endocrinologists in Canada are governed by, and also govern themselves through discourses of good diabetes care. Data collection, conducted from September 2014 to April 2017, involved analysis of formal documents and 15 semi-structured interviews with family physicians and endocrinologists. Analysis was informed through Dean’s (2010) analytics of government. My findings reveal shifts in the expected conduct of physicians over the past ninety years related to dominant discourses in different historic times. My analysis makes visible the material effects, diversity, contradictions and conflicts as physicians enact historically-constituted roles to engage with PWDs as both passive recipients of care and active participants in care. I bring attention to how discourses of good diabetes care intersect and intertwine in ways that have implications for the success of diabetes knowledge translation initiatives, the intraprofessional relationship between family physicians and endocrinologists, and the provision of patient- centered care.
Development of Bioanalytical Assays for Biomolecular Interactions Using Surface Plasmon Resonance
Keywords: Alzheimer's disease
biomolecular interaction
electrochemical impedance spectroscopy
surface plasmon resonance

This thesis explores the applicability of surface plasmon resonance (SPR) with the aim to improve and suggest novel improvements in the subject matter with respect to biomolecular interactions. Such analytical techniques could be applied in the field of environmental, biological, and pharmaceutical chemistry, as well as surface science. In the first chapter, the backgrounds of Legionella pneumophila and Alzheimer’s disease (AD) were introduced. The chapter also described the key physical and chemical aspects of SPR and electrochemical impedance spectroscopy (EIS). Based on these analytical techniques, we explored the interactions of Legionella collagen-like (Lcl) proteins with glycosaminoglycans in Chapter 2. Moreover, the effect of tandem repeat units and self-aggregation analysis of Lcl proteins was also performed using SPR. Chapter 3 looked at the interaction of two AD-related proteins, amyloid-beta (Aβ) and apolipoprotein E4 (ApoE4). The interaction between these two proteins has been hypothesized to play a significant role in the early stages of AD. Lastly, from the practice of surface-based analytical techniques, an improvement in surface chemistry was suggested to achieve better sensitivity and anti-non-specific adsorption (anti-NSA) properties. A novel surface modification linker for gold surfaces was synthesized by our group to have improved stability and anti-NSA characteristics as described in Chapter 4. The linker was synthesized and characterized to support structure and function. The anti-NSA properties of the novel linker were demonstrated by both SPR and cyclic voltammetry (CV). To optimize the performance on studying protein-protein and protein-small molecule interactions, it would be most ideal to use our linker in conjunction to a surface spacer. In the end, we concluded the findings from the above-mentioned research studies and the future directions on those topics were expressed in detail (Chapter 5).