VictorJuiz/thesis huggingface dataset:
Validating Integrated Human Performance Models Involving Time-critical Complex Systems
Keywords: Human Performance Model
Validation
Time Sensitive Tasks
Complex System Operations

The current research sets out to demonstrate a comprehensive approach to validate complex human performance models as applied to time-sensitive tasks. This document is divided into 4 sections. Section 1 (Chapters 1 – 3) outlines previous efforts in the literature that have attempted to validate complex human performance models in the field with an emphasis on manual control models, task network models, cognitive models and integrated architectures. Section 2 (Chapters 4 – 7) elaborates on a validation approach and applies it to a baseline model of a complex task in the air traffic control domain. Section 3 (Chapters 7-12) outlines the importance of adopting an iterative model development-model validation process and reports on the three model iterations in an attempt to improve the validity of the baseline model. Each model augmentation was validated using the same validation approach and measures that were defined in Section 2. Section 4 (Chapters 13-14) provides a discussion and interpretation of the model results and highlights contributions to the field of both model validation and the field of human performance modelling of complex systems.
Left/Right Asymmetries in a Multidimensional Universe: Citizens, Activists, and Parties
Keywords: Left/Right
Party Policy
Public Opinion
Political Competition
Canadian Party Politics

Political scientists have sought to unify under a single theoretical umbrella the explanations for the patterns of public opinion in the electorate and the patterns of party policy. Yet, these models have not taken account of potential differences between left-wingers and right-wingers in the ways that policy preferences are bundled together across multiple dimensions of political disagreement. The dissertation examines the origins and structure of political opinions on three dimensions of left/right disagreement: wealth redistribution, social morality, and immigration. The overall argument is that the content and structure of opinions are fundamentally intertwined. As a result, left/right disagreement is multidimensional and asymmetrical. Left-wingers and right-wingers derive from different sources, and structure in different ways, their opinions about policy. These asymmetries appear in the patterns of public opinion, the preferences of party activists, and in the positioning of political parties.
Debt Financing, Bankruptcy Reorganization and Corporate Investment
Keywords: Corporate Finance
Corporate Investment
Debt Overhang
Underinvestment
Dynamic Panel Models
Corporate Bankruptcy
Chapter 11

In this thesis, I investigate economic and policy implications of corporate debt financing. In the first chapter, I examine whether or not leverage has a negative effect on corporate investment due to a debt overhang problem. Existing empirical studies face a challenging endogeneity problem inherent in the investment-leverage relationship, the source of which is the firm's anticipation of its growth opportunities. I develop a novel approach to control for this problem by using analysts' earnings forecasts as an anticipation measure. I show that anticipations influence the investment-leverage relationship in that firms that do anticipate future growth opportunities suffer less from debt overhang. In the second chapter, I extend Chapter One's analysis to a dynamic setting. I first establish that there is a stable long-term relationship between investment and leverage, and then disentangle the short-term dynamics of leverage and investment and find that the deviation of leverage from its benchmark path has a negative impact on the change in investment. I also employ dynamic panel models to estimate the causal dynamic effects of leverage on investment. The estimations show that the impact is negative for recent leverage, but positive for leverage in the more distant past. Also, the effects of leverage are attenuated when the investment uncertainties are further controlled. This suggests that the firm's response to investment uncertainties might explain dynamic effects of leverage on investment. In Chapter Three, I investigate the effects of the U.S. Chapter 11 bankruptcy-reorganization law on firm operating performance, and adopt matching methods to account for self-selection and heterogeneity in firms' pre-filing characteristics. Matching methods entail the selection of a control group of non-bankrupt firms that are comparable to Chapter 11 filing firms in a wide range of pre-filing characteristics that affect filing decisions. Comparing the operating performances of the two groups, I find that filing firms' net cash flows, but not operating incomes, improve significantly during bankruptcy. Furthermore, firms reduce their leverage levels and incur lower interest expenses after bankruptcy. The results suggest that the reduction in interest expenses contributes to the improvement in firms' net cash flows during bankruptcy.
New Insights into the Structure, Function and Evolution of TETR Family Transcriptional Regulators
Keywords: antibiotic resistance
allosteric mechanism
TetR
ligand screen

Antibiotic resistance is a worsening threat to human health. Increasing our understanding of the mechanisms causing this resistance will be of great benefit in designing methods to evade resistance and in developing new classes of antibiotics. In this thesis, I have used the TetR Family Transcriptional Regulators (TFRs), which constitute one of the largest antibiotic resistance regulator families, as a model system to study the structure, function and evolution of antibiotic resistance determinants. I performed a thorough examination of the variation and conservation seen in TFR sequences and structures using computational approaches. Through structure comparison, I have identified the most conserved features shared by the TFR family that are crucial for their stability and function. Based on my findings on conserved TFR structural features, a quantitative assay of binding affinity determination was developed. Through sequence comparison and a residue contact map method, I discovered the existence of a conserved residue network that correlates well with the known allostery pathway of TetR. This predicted allosteric communication network was experimentally tested in TtgR. I have also developed methods to identify TFR operator sequences through genomic comparisons and validated my prediction through experiments. In addition, I have developed an in vivo system that can be used to identify and characterize proteins that mediate resistance to almost any antibiotic. This system is simple, fast, and scalable for high-throughput applications, and could be used to discover a wide range of novel antibiotic resistance mechanisms. The principles that I applied to the TFR family could also be applied to other protein families.
Mapping SH3 Domain Interactomes
Keywords: proteomics
SH3 domain
interactome
protein-protein interaction
yeast two-hybrid
pooling
yeast
worm

Src homology 3 (SH3) domains are one family of the peptide recognition modules (PRMs), which bind peptides rich in proline or positively charged residues in the target proteins, and play important assembly or regulatory functions in dynamic eukaryotic cellular processes, especially in signal transduction and endocytosis. SH3 domains are conserved from yeast to human, and improper SH3 domain mediated protein-protein interaction (PPI) leads to defects in cellular function and may even result in disease states. Since commonly used large-scale PPI mapping strategies employed full-length proteins or random protein fragments as screening probes and did not identify the particular PPIs mediated by the SH3 domains, I employed a combined experimental and computational strategy to address this problem. I used yeast two-hybrid (Y2H) as my major experimental tool, as well as individual SH3 domains as baits, to map SH3 domain mediated PPI networks, “SH3 domain interactomes”. One of my important contributions has been the improvement for Y2H technology. First, I generated a pair of Y2H host strains that improved the efficiency of high-throughput Y2H screening and validated their usage. These strains were employed in my own research and also were adopted by other researchers in their large-scale PPI network mapping projects. Second, in collaboration with Nicolas Thierry-Mieg, I developed a novel smart-pooling method, Shifted Transversal Design (STD) pooling, and validated its application in large-scale Y2H. STD pooling was proven to be superior among currently available methods for obtaining large-scale PPI maps with higher coverage, high sensitivity and high specificity. I mapped the SH3 domain interactomes for both budding yeast Saccharomyces cerevisiae and nematode worm Caenorhabditis elegans, which contain 27 and 84 SH3 domains, respectively. Comparison of these two SH3 interactomes revealed that the role of the SH3 domain is conserved at a functional but not a structural level, playing a major role in the assembly of an endocytosis network from yeast to worm. Moreover, the worm SH3 domains are additionally involved in metazoan-specific functions such as neurogenesis and vulval development. These results provide valuable insights for our understanding of two important evolutionary processes from single cellular eukaryotes to animals: the functional expansion of the SH3 domains into new cellular modules, as well as the conservation and evolution of some cellular modules at the molecular level, particularly the endocytosis module.
Monitoring and Diagnosis for Autonomic Systems: A Requirement Engineering Approach
Keywords: monitor
diagnosis
autonomic computing
self-reconfiguration

Autonomic computing holds great promise for software systems of the future, but at the same time poses great challenges for Software Engineering. Autonomic computing research aims to design software systems that self-configure, self-repair, self-optimize and self-protect, so as to reduce software maintenance cost while improving performance. The aim of our research is to develop tool-supported methodologies for designing and operating autonomic systems. Like other researchers in this area, we assume that autonomic system architectures consist of monitoring, analysis/diagnosis, planning, and execution components that define a feedback loop and serve as the basis for system self-management. This thesis proposes an autonomic framework founded on models of requirements and design. This framework defines the normal operation of a software system in terms of models of its requirements (goal models) and/or operation (statechart models). These models determine what to monitor and how to interpret log data in order to diagnose failures. The monitoring component collects and manages log data. The diagnostic component analyzes log data, identifies failures, and pinpoints problematic components. We transform the diagnostic problem into a propositional satisfiability (SAT) problem solvable by off-the-shelf SAT solvers. Log data are preprocessed into a compact propositional encoding that scales well with growing problem size. For repair, our compensation component executes compensation actions to restore the system to an earlier consistent state. The framework repairs failures through reconfiguration when monitoring and diagnosis use requirements. The reconfiguration component selects a best system reconfiguration that contributes most positively to the system's non-functional requirements. It selects a reconfiguration that achieves this while reconfiguring the system minimally. The framework does not currently offer a repair mechanism when monitoring and diagnosis use statecharts. We illustrate our framework with two medium-sized, publicly-available case studies. We evaluate the framework's performance through a series of experiments on randomly generated and progressively larger specifications. The results demonstrate that our approach scales well with problem size, and can be applied to industrial sized software applications.
Decoherence in Optically Excited Semiconductors: a Perspective from Non-equilibrium Green Functions
Keywords: Decoherence
Semiconductor Optics
Non-equilibrium Green functions
Ultrafast electron dynamics

Decoherence is central to our understanding of the transition from the quantum to the classical world. It is also a way of probing the dynamics of interacting many-body systems. Photoexcited semiconductors are such systems in which the transient dynamics can be studied in considerable detail experimentally. Recent advances in spectroscopy of semiconductors provide powerful tools to explore many-body physics in new regimes. An appropriate theoretical framework is necessary to describe new physical effects now accessible for observation. We present a possible approach in this thesis, and discuss results of its application to an experimentally relevant scenario. The major portion of this thesis is devoted to a formalism for the multi-dimensional Fourier spectroscopy of semiconductors. A perturbative treatment of the electromagnetic field is used to derive a closed set of differential equations for the multi-particle correlation functions, which take into account the many-body effects up to third order in the field. A diagrammatic method is developed, in which we retain all features of the double-sided Feynman diagrams for bookkeeping the excitation scenario, and complement them by allowing for the description of interactions. We apply the formalism to study decoherence between the states of optically excited excitons embedded in an electron gas, and compare it with the decoherence between these states and the ground state. We derive a dynamical equation for the two-time correlation functions of excitons, and compare it with the corresponding equation for the interband polarization. It is argued, and verified by numerical calculation, that the decay of Raman coherence depends sensitively on how differently the superimposed exciton states interact with the electron gas, and that it can be much slower than the decay of interband polarization. We also present a new numerical approach based on the length gauge for modeling the time-dependent laser-semiconductor interaction. The interaction in the length gauge involves the position operator for electrons, as opposed to the momentum operator in the velocity gauge. The approach is free of the unphysical divergences that arise in the velocity gauge. It is invariant under local gauge symmetry of the Bloch functions, and can handle arbitrary electronic structure and temporal dependence of the fields.
The Concept of Living Liberation in the Tirumantiram
Keywords: liberation
Tamil literature
tantra/agama
Saivisim
yoga
bhakti
symbolism

This dissertation examines the concept of living liberation in the Tirumantiram, a work recognised as one of the Tamil Saiva canonical texts composed around the ninth century. Modern scholarship has thus far attempted to comprehend the Tirumantiram in terms of the post-Tirumantiram traditions that developed after the thirteenth century: Tamil Saiva Siddhànta and Tamil Siddha. Consequently, the unity and coherence of the text are subjected to question, and the dual literary and cultural roots of the Tirumantiram remain largely uninvestigated. Besides, the significance of the Tirumantiram as one of the earliest vernacular works directly dealing with the question of soteriology for Tamil speaking populace, most of whom are not qualified for liberation and preceptorhood according to the Saivàgamas with which the text identifies itself, is not fully recognised. This dissertation argues that the concept of living liberation constitutes the unifying theme of the Tirumantiram, which is an outcome of the synthesis of Tamil and Sanskrit traditions, and demonstrates that the Tirumantiram-which does not apparently promote the ideology of temple cult around which the Tamil bhakti movement and Saivàgamas of Southern Saivism developed–exemplifies an alternative religious vision centred on the human body. This dissertation consists of four chapters. The first chapter examines the Tamil legacy to the concept of living liberation. The second examines the ambiguous relations between the Sanskrit traditions and the Tirumantiram. How the Tamil and Sanskrit traditions are fused together to produce a unique version of yoga, the means to attain living liberation, is the concern of the third chapter. The final chapter establishes through an analysis of sexual symbolism expressed in connotative language that the Tirumantiratm is an esoteric text. Thus, the Tirumantiram reflects the blending of an esoteric tantric sect with the leading mainstream bhakti religion, probably to win approval of and recognition in the Tamil Saiva community during the medieval period.
Lifestyle and Breast Cancer Risk Factors in Postmenopausal Caucasian and Chinese-Canadian Women
Keywords: Breast Cancer Risk Factors
Lifestyle
Chinese
Postmenopausal women

Striking differences exist between countries in the incidence of breast cancer, with rates higher in the West than in Asian countries. The causes of these differences are unknown, but because incidence rates change in migrants, they are thought to be due to lifestyle rather than genetic differences. The objective of this thesis was to compare established breast cancer risk factors, physical activity, and diet in three groups of postmenopausal women at substantially different risks of developing breast cancer – Caucasians (N = 413), Chinese born in the West or who migrated to the West before age 21 (N = 216), and recent Chinese migrants, 99% of whom coming from urban China (N = 421). In this cross-sectional study, information on risk factors and diet were collected by telephone, and physical activity and anthropometric data were obtained at a home visit. Compared to Caucasians, recent Chinese migrants weighed on average 14 kg less, were 6 cm shorter, had menarche a year later, were more often parous, and less often had a family history of breast cancer or a benign breast biopsy. Estimating 5-year absolute breast cancer risks using the Gail Model showed that risk estimates in Caucasians would be reduced by only 11% if they had the risk factor profile of recent Chinese migrants for the variables in the Gail Model. Compared to Caucasians, recent Chinese migrants had lower average total physical activity over lifetime, and also spent less time on moderate- and vigorous-intensity activity. Compared to Caucasians, recent Chinese migrants consumed per day on average 175 fewer calories, 6 more grams of energy-adjusted protein, 16 more grams of energy-adjusted carbohydrates, and 5 fewer grams of energy-adjusted fat. Also, recent Chinese migrants consumed higher amounts of grains, fruits, vegetables, fish, and soy products, and lower amounts of alcohol, meat, dairy products, and sweets than Caucasians. Western born Chinese and early Chinese migrants had values intermediate between the other two groups for most of the variables. These results suggest that in addition to the established risk factors, some dietary factors may also contribute to the lower breast cancer risk in urban Chinese women.
Invasion-induced Changes to the Offshore Lake Ontario Food Web and the Trophic Consequence for Bloater (Coregonus hoyi) Reestablishment
Keywords: food web
trophic ecology
Lake Ontario
invasives
bloater reestablishment
mass-balance

I compared changes in offshore Lake Ontario major species-group biomass, production and diets before (1987-1991) and after (2001-2005) invasion-induced ecological change. I synthesized the observations into carbon-based mass-balanced food webs linking two pathways of energy flow; the grazing chain (phytoplankton-zooplankton-fish) and the microbial loop (autotrophic bacteria-heterotrophic protozoans) and determined how the structure and function of the food web changed between time-periods. I use the food web descriptions to simulate the reestablishment of native deepwater bloater. I developed empirical models describing spatial variation in temperature and applied them to investigate predator temperature distributions, bioenergetic consequences of alewife diet and distribution shifts, and zooplankton productivity. Primary production declined as did the biomass and production of all species-groups except Chinook salmon. Total zooplankton production declined by approximately half with cyclopoid copepod production declining proportionately more. Zooplankton species richness and diversity were unaffected. Alewife adapted to low zooplankton production by consuming more Mysis, increasing their trophic level. The increased prey-size and exploitation of spatial heterogeneity in resource patches and temperature may have allowed alewife to maintain their growth efficiency. The trophic level also increased for smelt, adult sculpin, adult alewife and Chinook salmon. Phytoplankton grazing rates declined and predation pressure increased on Mysis, adult smelt and alewife, and decreased on protozoans. Resource to consumer trophic transfer efficiencies changed; increasing for protozoans, Mysis, Chinook salmon and other salmonines and decreasing for zooplankton, prey-fish and benthos. The changes suggest both bottom-up and top-down influences on food web structure. The direct trophic influences of invasive species on the offshore Lake Ontario food web were minor. Carbon flows to Mysis indicated an important, and changing ecological role for this species and we hypothesize that Mysis may have contributed to Diporeia declines. Simulations suggest that only a small reestablished bloater population, limited by Diporeia production, could be sustained.
Acceleration of Iterative Methods for Markov Decision Processes
Keywords: Markov Decision Processes

This research focuses on Markov Decision Processes (MDP). MDP is one of the most important and challenging areas of Operations Research. Every day people make many decisions: today's decisions impact tomorrow's and tomorrow's will impact the ones made the day after. Problems in Engineering, Science, and Business often pose similar challenges: a large number of options and uncertainty about the future. MDP is one of the most powerful tools for solving such problems. There are several standard methods for finding optimal or approximately optimal policies for MDP. Approaches widely employed to solve MDP problems include value iteration and policy iteration. Although simple to implement, these approaches are, nevertheless, limited in the size of problems that can be solved, due to excessive computation required to find close-to-optimal solutions. My thesis proposes a new value iteration and modified policy iteration methods for classes of the expected discounted MDPs and average cost MDPs. We establish a class of operators that can be integrated into value iteration and modified policy iteration algorithms for Markov Decision Processes, so as to speed up the convergence of the iterative search. Application of these operators requires a little additional computation per iteration but reduces the number of iterations significantly. The development of the acceleration operators relies on two key properties of Markov operator, namely contraction mapping and monotonicity in a restricted region. Since Markov operators of the classical value iteration and modified policy iteration methods for average cost MDPs do not possess the contraction mapping property, for these models we restrict our study to average cost problems that can be formulated as the stochastic shortest path problem. The performance improvement is significant, while the implementation of the operator into the value iteration is trivial. Numerical studies show that the accelerated methods can be hundreds of times more efficient for solving MDP problems than the other known approaches. The computational savings can be significant especially when the discount factor approaches 1 and the transition probability matrix becomes dense, in which case the standard iterative algorithms suffer from slow convergence.