VictorJuiz/thesis huggingface dataset:
Scalable Inference in Hardware Verification and Social Graph Reasoning
Keywords: GPU
Influence maximization
RTL
Triage
Verification

With the growing abundance of raw data and the increasing processing power of parallel computing systems, various industries nowadays embrace data mining and are rapidly replacing traditional methods with machine learning solutions. One area that is currently undergoing such transition is the semiconductor industry. In this domain several problems call for data-driven solutions, with failure triage being one of the most prominent. Failure triage is an emerging regression verification problem where the goal is to sort through thousands of hardware failures in order to characterize and prioritize them before they are analyzed in detail and fixed. This preprocessing step is critical in deciding how resources (i.e., engineering effort) will be allocated in fixing these failure. Today, industries assign these decisions to expert engineers. Such manual approaches are unsustainable long-term with design complexity on the rise and verification data becoming more and more sensitive to human interpretation. In the first part of this thesis we show that existing inference methods can be employed towards automating failure triage. Experiments demonstrate that the proposed inference methods can make correct decisions at various triage stages with at least 80% average accuracy, and only a 6.5% runtime overhead when used in modern debugging flows. In contrast to the semiconductor industry, a long thread of work based on data mining has already been established in the social media analytics sector, with applications ranging from sentiment analysis to community detection and viral marketing. In the second part, we study one of the dominant problems in computational social science, known as influence maximization. The problem relates to identifying a subset of a population that can spread information over a social network in a maximal way. We address influence maximization in the continuous-time domain, where the propagation of influence between members of the population obeys stochastic transmission times. Maximizing influence in the continuous-time domain is generally intractable and, therefore, the process calls for approximations. This dissertation proposes novel approximation algorithms that are specifically tailored for parallel computing, and that achieve between 5x-85x performance improvements over the state-of-the-art.
The Role of Infections in the Etiology of Childhood Acute Lymphoblastic Leukemia
Keywords: administrative data
Childhood acute lymphoblastic leukemia
etiology
Infections
systematic review and meta analysis
validation

Childhood acute lymphoblastic leukemia (ALL) is the most common childhood cancer. However, the etiology of childhood ALL is uncertain. An infectious trigger for ALL is hypothesized based on evidence from biological and epidemiologic studies. The goal of the dissertation was to assess the relationship between prior infections and the development of childhood ALL. In a systematic review and meta-analysis, no overall relationship between prior infections and childhood ALL could be identified (odds ratio, OR=1.10, 95% confidence interval, CI 0.95-1.28). The systematic review showed most studies that used self-reported data to measure infections were susceptible to recall bias. Thus, administrative data may be particularly useful in furthering our understanding of the infectious etiology of ALL. Using electronic medical records as the reference standard, a study was conducted to assess the criterion validity of administrative databases to identify infectious syndromes in children aged 0-18 years from Ontario, Canada. Administrative billings codes for an infection (respiratory, skin and soft tissue, gastrointestinal, urinary tract or otitis externa) demonstrated moderate sensitivity (0.74, 95%CI 0.70-0.77), and high specificity (0.95, 95%CI 0.93-0.96), positive predictive value (0.87, 95%CI 0.84-0.90), and negative predictive value (0.88, 95%CI 0.86-0.89). Finally, the association between prior infections and the development of childhood ALL, using health administrative data, was conducted applying the findings from the validation study to define and measure infections. Overall, having >2 infections per year increased odds of ALL by 43% compared to children with ≤0.25 infections per year in Ontario. Infections occurring between 1 to 1.5 years of life may be a critical period as having an infection in this window increased the odds of ALL by 20%. Certain infections such as respiratory and invasive infections may be more important than other infections in the development of ALL. The accumulated insights from each study was used to inform subsequent objectives, resulting in a unified dissertation that found infections have a role in the etiology of childhood ALL. Future work should extend the empirical study investigate the critical period between 1 to 1.5 years by collecting detailed infection data and other exposures that begin around this period.
A Heuristic Approach to Explore: Value of Perfect Information
Keywords: Bellman Equation
Exploration-Exploitation Tradeoff
Forward-looking Behavior
Heuristics
Multi-armed bandit
Value of Perfect Information

How do consumers choose in a dynamic stochastic environment when they face uncertainty about the return from their choice? The classical solution to this problem is to assume consumers use dynamic programming to obtain the optimal decision rule. However, this approach has two drawbacks. First, it is computationally very expensive to implement because it requires solving a dynamic programming problem with a continuous state space. Second, a decision maker is assumed to behave “as if” she optimally processes information regardless of its cognitive tractability. To address these two issues, we propose a new heuristic decision process called Value of Perfect Information (VPI), which extends the idea first proposed by Howard (1966) in the engineering literature. This approach provides an intuitive and computationally tractable way to capture the value of exploring uncertain alternatives. Intuitively, in VPI, a decision maker investigates a subset of information which is expected by her to improve her myopic decision outcome. We argue that our VPI approach provides a “fast and frugal” way to balance the trade-off between exploration versus exploitation. More specifically, the VPI approach only involves ranking the alternatives and computing a one-dimensional integration to obtain the expected future value of exploration. In terms of computational costs, we show that the VPI approach is significantly simpler than the standard dynamic programming approach, making it a very practical learning model for consumers to employ. Also, the VPI approach captures asymmetric switching patterns with respect to price promotions in the data. Using individual-level scanner data, we find evidence that our VPI approach is able to capture consumers' choice well.
Alexander Invariants of Tangles via Expansions
Keywords: Alexander Polynomials
Fox Milnor
Gamma Calculus
Knots
Ribbon
Tangles

This thesis consists of two parts. In the main part of the thesis we introduce an extension of the Alexander polynomial to tangles, known as Γ-calculus or Gassner calculus, which has appeared in [BNS13, Hal16] and various talks by Prof Bar-Natan. Our main object of study is w-tangles, which we describe using the language of meta-monoids (see [BNS13, BN15a, Hal16]). There is a map from usual tangles to w-tangles and so an invariant of w-tangles induces an invariant of usual tangles. Using the language of Γ-calculus, we rederive certain important properties of the Alexander polynomial, most notably the Fox-Milnor condition on the Alexander polynomials of ribbon knots [Lic97, FM66]. We argue that our proof has some potential for generalization which may help tackle the slice-ribbon conjecture. In a sense this thesis is an extension of [BNS13]. In the second part of the thesis, we study the associated graded space of w-tangles, which is the space of arrow diagrams [BND16, BND14]. We describe an expansion of w-tangles, i.e. a map from w-tangles to its associated graded space. The concept of expansions is inspired by the Taylor expansions, and w-tangles have a much simpler expansion than usual tangles (for usual tangles an expansion is given by the Kontsevich integral [Oht02]). There is a relationship between arrow diagrams and Lie algebras. Using the expansion of w-tangles we recover Γ-calculus by choosing a particular Lie algebra, namely the two-dimensional non-abelian Lie algebra. We give a commutative diagram that summarizes the spaces and maps involved. The second part of the thesis is more or less independent of the first part.
Falls in Community-dwelling Older Adults with Cancer: Impact on Cancer Treatment, Circumstances, Assessment, Management, and Reporting
Keywords: aging
Cancer
falls
geriatrics

Falls are major health issues among older adults and even more so in older cancer patients due to cancer and its treatment. Knowledge on circumstances surrounding falls and fear of falling is vital for understanding how various factors may precipitate falls and for informing development of effective interventions to prevent falls in this population. Delays in cancer treatment caused by fall injuries may have significant implications on disease trajectory and patient outcomes. However, a systematic review found gaps in knowledge in terms of how falls impact cancer treatment in this population. The aim of this research was to explore the circumstances of falls and fear of falling in community-dwelling older adults with cancer, as well as to examine how falls are assessed, reported, and managed in outpatient oncology clinics, and how falls might impact cancer treatment in this population. A cross-sectional study using a convergent-parallel mixed-methods design was conducted at the Princess Margaret Cancer Centre in Toronto, Canada. Data were collected by self-reported survey, chart review, and open-ended interviews. One hundred older adults (aged >=65) and 14 oncologists participated in this study. Falls were not commonly reported by patients to their oncologists (43%), and were rarely assessed by oncologists (7%). One in twenty who fall appears to lead to change in cancer management. However, falls were not commonly reported by patients nor prioritized by oncologists. Older patients perceived falls as minor incidents not worth mentioning (57%). When a fall was reported, oncologists’ actions included determining cause of falls (64%), asking circumstances of falls (36%), and referrals (29%). Oncologists indicated that the majority of older patients were not forthcoming in reporting falls. Circumstances of falls seem to be similar to those in the general geriatric population. This research shows that incorporating routine fall assessment in oncology clinic appointments may help identify those at risk for falls so that timely interventions can be triggered. Additionally, strategies for fall prevention and management used in the general geriatric population can potentially benefit this population as well. Attention may be warranted regarding medication review, health-teaching on fall safety, home evaluation, and referral for balance training.
Behavioural Foundations of Elite Politics: How Individual-Level Characteristics Shape the Decision Making of Elected Politicians
Keywords: Accountability
Behaviour
Bias
Decision making
Experiments
Politicians

What kind of decisions makers are elected politicians? Do they exhibit the same cognitive biases and choice anomalies that plague the reasoning of everyday citizens? Do they acquire some degree of expertise that makes their decision making systematically different? And what explains differences between different groups of politicians in how they confront policy problems and other in-office challenges? This dissertation consists of five papers that attempt to provide empirical answers for these questions from an individual-level behavioural perspective. These papers use evidence derived principally from in-person and online experiments conducted with hundreds of incumbent politicians and thousands of citizens in four countries. I find that politicians are equally susceptible as citizens to a series of policy-critical choice anomalies, including equivalency framing effects, the status-quo bias, escalation of commitment in face of sunk costs, and discounting future payoffs. In some cases they exhibit certain biases even more strongly than non-elites. I further document systematic differences between politicians in these domains, in ways that are directly tied to being held politically accountable and to the nature of their elected office: representatives who are more overconfident regarding their likelihood of being re-elected exhibit stronger risk-seeking behaviour; local officials who report an interest in future office-holding are strongly responsive to accountability cues, resulting in greater willingness to take risks, while those who are uninterested in re-election exhibit no behaviour change; and female and male politicians respond in opposite ways to being held publicly accountable, with men being significantly more likely to abandon policy choices presented as the status quo, and women becoming more entrenched in it. Finally, I use a formal model to analyze the implication of heterogeneity among elected officials in their capacity to engage in strategic reasoning in the context of elite frame production. Together, the papers in this dissertation provide an empirically-grounded and nuanced set of insights on elite decision making in politics that question the adequacy of numerous influential political science models and theories, which have either been relying on untested assumptions regarding elite behaviour, or have overlooked them altogether.
Using Network Theory to Manage Knowledge from Unstructured Data in Construction Projects: Application to a Collaborative Analysis of the Energy Consumption in the Construction of Oil and Gas Facilities
Keywords: blockmodeling
construction management
energy use
knowledge retrieval and representation
network analysis
unstructured data

This research provides an approach to capture the knowledge in unstructured data related to the energy consumption in the construction of oil and gas projects. Because of the challenges of this industry in managing knowledge more efficiently, this work is relevant for planning/assessments during the construction of future projects. As a starting point, a concept map, which organizes thirty-four construction activities, systems, and factors that influence energy consumption during the construction, is presented. This concept map is a simplified taxonomy that guarantees consistency across different projects. As such, three case studies of oil and gas projects are conducted based on semi-structured interviews to design the respective concept networks. The method represents the concepts in the form of a network. The nodes of the network are the thirty-four concepts, and a tie is defined whenever there is a relationship between two concepts that impact the energy consumption in the construction stage. Network analysis is used to retrieve the knowledge, which is contextualized in the case-based projects. Then, the networks of the three cases are compared with a baseline, which was developed using an expert survey. With the survey focusing on the experts' general knowledge, blockmodeling is used to capture knowledge constructs in each case network. The research is evaluated using a test with one of the case studies and a system as an online interface for collaboration. The results collected from a questionnaire and a focus group with the participants of the test indicate that the proposed approach is satisfactory. Although this study is not an energy assessment, each project has its unique, contextual network; therefore, comparing them with the network of future projects constitutes a valuable source of knowledge. This work also highlights the importance of supporting collaboration between project team members to study and decide on the plans to manage/reduce energy consumption during the construction phase in oil and gas facilities. While the energy savings are smaller than the upstream and operation phases, it has received much less attention. It is also a phase with much more subjective and contextualized knowledge – making the use of case-based analyses more suitable.
Engaging patient in health and health care processes: the role of patient platforms
Keywords: Patient engagement
Social media platforms

Background: Health-specific social media platforms, referred to as patient platforms (PPs), are now freely available on the Internet to engage users in their health care process; yet, little is known about what they are trying to achieve, for whom they are designed, and how they attempt to achieve their goals. Methods: Qualitative methods were used to analyze textual and visual data (e.g., platform policies and other relevant webpages) collected from a purposive sample of eleven PPs stratified by various attributes (for-profit/not-for-profit, single/multiple conditions, different conditions). Data were systematically tracked and rigorously analyzed according to Framework Analysis methodology. Results: The study identified a framework for mapping tools. It also revealed that PPs connected users in what was referred to as communities, to share information on specific medical conditions. Forums were the main tools connecting users. Some PPs offered simple forums for posting questions and answers whereas others offered forums for ongoing discussions. Besides supporting patients, PPs were also noted as a channel for delivering advertisements and marketing material directly to patients. Lastly, platform tools have the potential to engage and empower patients to take on an expanded role but can also be oriented towards supporting the platforms’ own interests, and the interests of their sponsors. Discussion: The emergent framework described in this study can be used to support the design of future tools for better engaging patients. Second, users may not be aware of other platform interests without reading or understanding policies to which users are required to consent. Finally, advertisements provided through PPs can affect the health of patients and the health care system in various ways, both positive and negative. More research is needed in this evolving area to better understand the impacts on the health of patients and the health care system.
PARVALBUMIN-POSITIVE INTERNEURONS MEDIATE NEOCORTICAL-HIPPOCAMPAL INTERACTIONS THAT ARE NECESSARY FOR MEMORY CONSOLIDATION
Keywords: Interneurons
Memory
Oscillations
Ripple-spindle coupling

Following learning, increased coupling between spindle oscillations in the medial prefrontal cortex (mPFC) and ripple oscillations in the hippocampus is thought to underlie memory consolidation. However, whether learning-induced increases in ripple-spindle coupling are necessary for successful memory consolidation has not been tested directly. In order to de- couple ripple-spindle oscillations, here we chemogenetically inhibited parvalbumin-positive (PV+) interneurons, since their activity is important for regulating the timing of spiking ac- tivity during oscillations. We found that contextual fear conditioning increased ripple-spindle coupling. However, inhibition of PV+ cells in either CA1 or mPFC eliminated this learning- induced increase in ripple-spindle coupling without affecting ripple or spindle incidence. Consistent with the hypothesized importance of ripple-spindle coupling in memory consol- idation, post-training inhibition of PV+ cells disrupted contextual fear memory consolidation. These results indicate that successful memory consolidation requires coherent hippocampal- neocortical communication mediated by PV+ cells.
The Electronic and Optical Properties of Graphene Flakes and Similar Systems
Keywords: graphene
nanostructures
organic materials
single-photon sources

Organic materials have garnered interest from physicists, chemists, and engineers due to their remarkable electronic properties and potential optical applications. To accurately describe the electronic and optical properties of these systems, electron correlations beyond the mean-field level must be included. In this thesis, we focus on three systems: dibenzoterrylene, rectangular graphene flakes, and -acene molecules. We use the Pariser-Parr-Pople model to describe the electrons and apply a configuration interaction strategy to solve for the many-body wavefunctions of these systems. We first investigate the optical properties of dibenzoterrylene (DBT); DBT is of interest as a possible single-photon source. We calculate the linear absorption spectrum and the spatial distributions of the electrons involved in several bright transitions. We determine the two-photon absorption spectrum and show there are several states that are bright due to two-photon absorption. We predict that there are no competing optical processes that might hinder the single-photon source application of DBT. Next, we focus on the electronic and optical properties of rectangular graphene flakes. We find that the lowest energy bright transition has a transition dipole moment that is polarized along the long axis of the flake, but the charge distributions involved in these transitions are invariably localized on the zigzag edges. We investigate the role of impurities on the optical properties of these graphene flakes; we find that impurities located on the zigzag edges can have a significant - and often dramatic - impact on the optical properties of these systems. Finally, we study the optical properties of tetracene, pentacene, and hexacene, known as the -acenes. We compute the one-photon absorption spectra of the -acenes and compare our results with other quantum chemistry calculations. We calculate the charge densities involved in the bright transitions. We determine the two-photon absorption spectra and show that there are two two-photon active states in the low energy regime. We identify simple qualitative features in the optical properties of the -acenes which can be easily understood.