VictorJuiz/thesis huggingface dataset:
Development and Application of Hidden Markov Models in the Bayesian Framework
Keywords: Hidden Markov model

This thesis develops new hidden Markov models and applies them to financial market and macroeconomic time series. Chapter 1 proposes a probabilistic model of the return distribution with rich and heterogeneous intra-regime dynamics. It focuses on the characteristics and dynamics of bear market rallies and bull market corrections, including, for example, the probability of transition from a bear market rally into a bull market versus back to the primary bear state. A Bayesian estimation approach accounts for parameter and regime uncertainty and provides probability statements regarding future regimes and returns. A Value-at-Risk example illustrates the economic value of our approach. Chapter 2 develops a new efficient approach to model and forecast time series data with an unknown number of change-points. The key is assuming a conjugate prior for the time-varying parameters which characterize each regime and treating the regime duration as a state variable. Conditional on this prior and the time-invariant parameters, the predictive density and the posterior of the change-points have closed forms. The conjugate prior is further modeled as hierarchical to exploit the information across regimes. This framework allows breaks in the variance, the regression coefficients or both. In addition to the time-invariant structural change probability, one extension assumes the regime duration has a Poisson distribution. A new Markov Chain Monte Carlo sampler draws the parameters from the posterior distribution efficiently. The model is applied to Canadian inflation time series. Chapter 3 proposes an infinite dimension Markov switching model to accommodate regime switching and structural break dynamics or a combination of both in a Bayesian framework. Two parallel hierarchical structures, one governing the transition probabilities and another governing the parameters of the conditional data density, keep the model parsimonious and improve forecasts. This nonparametric approach allows for regime persistence and estimates the number of states automatically. A global identification algorithm for structural changes versus regime switching is presented. Applications to U.S. real interest rates and inflation compare the new model to existing parametric alternatives. Besides identifying episodes of regime switching and structural breaks, the hierarchical distribution governing the parameters of the conditional data density provides significant gains to forecasting precision.
Preparing Teacher Candidates for the Present: Exploring the Praxis of Mindfulness Training in Teacher Education
Keywords: mindfulness
teacher education
teacher disposition
holistic education

The fields of medicine and health care continue to demonstrate the benefits of mindfulness-based practice for stress reduction and well-being. Research is also beginning to reveal the professional benefits of mindfulness training with human service professionals, as well as the impact with children and youth, and more broadly within the field of education and human development. This qualitative action research study uses a grounded theory approach to elucidate the added value of the Mindfulness-Based Wellness Education (MBWE) program within three main areas of teacher education: dispositional development, content knowledge, and instructional repertoire. Two years being engaged in the iterative process of teaching, interviewing teacher candidates, and program development brought forth five main themes: (1) Personal and Professional Identity, Reflective Practitioner, (3) Constructivist Learning & Holistic Vision of Teaching, (4) Social and Emotional Competence on Practicum, and (5) Engagement in Teacher Education. Additional findings outline key curricular and pedagogical components of the MBWE program that facilitate teacher candidate learning. Finally, a holistic model of pedagogical well-being presents an avenue for understanding the integration of mindful wellness into teacher education, and the K-12 classroom.
Error-correcting Codes for Fibre-optic Communication Systems
Keywords: optical communications
coding theory
staircase codes
coded modulation

Electronic signal processing techniques have assumed a prominent role in the design of fibre-optic communication systems. However, state-of-the-art systems operate at per-channel data rates of 100 Gb/s, which constrains the class of communication algorithms that can be practically implemented. Relative to LDPC-like codes, product-like codes with syndrome-based decoding have decoder dataflow requirements that are smaller by more than two orders of magnitude, which strongly motivates the search for powerful product-like codes. This thesis presents a new class of high-rate binary error-correcting codes, staircase codes, whose construction combines ideas from convolutional and block coding. A G.709-compliant staircase code is proposed, and FPGA-based simulation results show that performance within 0.5 dB of the Shannon Limit is attained for bit-error-rates below 1E-15. An error-floor analysis technique is presented, and the G.709-compliant staircase code is shown to have an error floor below 1E-20. Using staircase codes, a pragmatic approach for coded modulation in fibre-optic communication systems is presented that provides reliable communications to within 1 bit/s/Hz of the capacity of a QAM-modulated system modeled via the generalized non-linear Schrodinger equation. A system model for a real-world DQPSK receiver with correlated bit-errors is presented, along with an analysis technique to estimate the resulting error floor for the G.709- compliant staircase code. By applying a time-varying pseudorandom interleaver of size 2040 to the output of the encoder, the error floor of the resulting system is shown to be less than 1E-20.
Technology Development for Next Generation Functional Analysis of Bioactive Molecules
Keywords: Yeast
Sequencing
Technology Development
Chemical Biology
Chemical Genetics
Drug Discovery

The genome-wide HaploInsufficieny Profiling (HIPHOP) technique has been validated as a method to quantify the relative abundance of uniquely tagged yeast deletion strains using a microarray readout. The massive throughput of next generation sequencing presents a new technology for assessing HIPHOP profiles. I developed a new method called Barcode analysis by Sequencing (Bar-seq) that applies deep sequencing to genome-scale fitness. I show that Bar-seq outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex genome-scale fitness assay, Bar-seq quantitatively identifies drug-targets, exceeding the performance of the microarray assay. I also established that Bar-seq is well suited to a multiplex format and provides a dramatic increase in throughput. I used the genome-wide HIPHOP assay and other functional genomics tools to explore the mechanisms underlying drug-drug synergies. Drug combination therapy, and synergistic combinations in particular, have several advantages over monotherapies. Synergistic drug combinations allow the dose of each agent to be reduced, often with the benefit of diminishing side effects while maintaining efficacy and decreasing the chances of drug resistance. I used my yeast model to identify synergistic drug combinations and found that inhibitors of ergosterol biosynthesis are highly synergistic with several agents, including those targeting other points within the same pathway. I also devised a method that enriches for synergistic interactions during screening of compound combinations. This new synergy prediction method can aid in the rapid identification of anti-proliferative combinations and can be readily applied to other organisms for further characterization and/or confirmation. Finally, I examined synergistic combination HIPHOP profiles and identified Gene Ontology enrichments that are combination-specific.
Contributions of Epstein-Barr Nuclear Antigen 1 (EBNA1) to Epithelial Cell Infections
Keywords: Epstein-Barr Virus
EBNA1
PML nuclear bodies
p53
EBV reactivation

Epstein-Barr virus (EBV) latent infection is associated with lymphoid and epithelial tumours, including nasopharyngeal carcinoma (NPC) and gastric carcinoma (GC). Since EBNA1 protein is expressed in all EBV tumours, I explored whether EBNA1 alters the cellular environment in ways that would contribute to the development of these epithelial tumours. I have shown that EBNA1 disrupts nuclear bodies (NBs) formed by the PML tumor suppressor and degrades PML proteins in a proteasome dependent manner in NPC and GC cell lines. I have verified the role of EBNA1 in disrupting PML NBs through overexpression and silencing of EBNA1 and shown that EBNA1 alone is sufficient to mediate these effects. Using EBNA1 mutants I found that USP7 and protein kinase CK2 (two enzymes that negatively regulate PML NBs) are important for EBNA1-mediated disruption of PML NBs. Furthermore, I have shown that EBNA1 localizes to PML NBs, and interacts with PML IV, which mediates the enrichment of USP7 and CK2β with PML NBs and increases CK2 phosphorylation of PML proteins, a known prerequisite for PML degradation. Consequently, functions downstream of PML were impaired in the presence of EBNA1. In particular, cells expressing EBNA1 had decreased levels of p53acetylation, p21 and apoptosis in response to DNA damage. Furthermore, DNA repair was markedly impaired in these cells, despite the fact that they survived better after induction of DNA damage than cells lacking EBNA1. In keeping with these observations, immunohistochemistry staining of GC biopsies showed that EBV-positive GC biopsies had lower PML staining compared to EBV-negative samples. These results show that EBNA1 directly affects host cell processes that would be expected to promote malignant transformation. Additionally, I have shown that EBNA1's ability to disrupt PML NBs is important for reactivation of EBV from latency; hence, is required for efficient spread of EBV from host to host.
Comprehension of Labrador Inuttitut Functional Morphology by Receptive Bilinguals
Keywords: Inuktitut
receptive bilinguals
heritage language
bilingualism
incomplete language acquisition

This study examines knowledge of grammar by receptive bilinguals (RBs) - heritage speakers who describe themselves as capable of fluent comprehension in Labrador Inuttitut (an endangered dialect of Inuktitut), but of little or no speech production in it. Despite the growing research on incomplete acquisition, RBs have yet to be studied as a specific population. Participants (8 fluent bilinguals, 17 RBs, 3 low-proficiency RBs) performed a morpheme comprehension task and a grammaticality judgment task. General measures of their comprehension and production abilities included a story retelling task as an overall assessment of comprehension, a vocabulary test, an elicited imitation task, and a production task. This data was complemented by language behaviour interviews. The results showed that RBs have good, though not perfect, comprehension and basic vocabulary, but speech production is very difficult for them. They have grammatical knowledge, but it is incomplete: Knowledge of some structures is robust, and their comprehension is fluent (past vs. future contrast, aspectual morphemes); others are missing (temporal remoteness degrees); and yet for others (case and agreement), RBs have the category and know its position in the word structure, but have difficulty connecting the features with the morphemes expressing them. These findings explain the significant asymmetry between comprehension and production in RBs: In comprehension, incomplete knowledge may result in loss of some aspects of meaning, but in many cases it can be compensated for by pragmatic knowledge and extralinguistic context, while in production, it can result in the selection of an incorrect morpheme or inability to select a morpheme. Low-proficiency RBs have partial comprehension, small vocabulary, and almost no production. They do not understand most functional morphemes; however, they show knowledge of the basic properties such as the position of the obligatory agreement marker on the verb. This study provides data on an understudied language and an understudied population at the extreme end of unbalanced bilingualism. The findings have implications both for the psycholinguistics of bilingualism and for language revitalization, especially in the context of a language shift in indigenous language communities, where RBs are often the last generation to have competence in the indigenous language.
Influence of Degradable Polar Hydrophobic Ionic Polyurethanes and Cyclic Mechanical Strain on Vascular Smooth Muscle Cell Function and Phenotype
Keywords: Vascular tissue engineering
Polyurethane elastomer
Vascular smooth muscle cells
Scaffold
Soft tissue biomechanics
Cell proliferation
Scaffold porosity
Cell Phenotype
Cyclic mechanical strain
Biodegradation
Crosslinking monomers
Tensile mechanical properties

Vascular tissue engineering (VTE) with the use of polymeric scaffolds offers the potential to generate small-diameter (<6 mm) arteries. In this thesis, a degradable polar hydrophobic ionic (D-PHI) polyurethane porous scaffold was synthesized with the objective of demonstrating its potential application for VTE. D-PHI scaffold synthesis was optimized, maximizing isocyanate and methacrylate monomer conversion. Through the incorporation of a lysine-based crosslinker, scaffold mechanical properties and swelling were manipulated. Furthermore, D-PHI scaffolds demonstrated the ability to support the growth and adhesion of A10 vascular smooth muscle cells (VSMCs) during two weeks of culture. This study also investigated the effect of a double porogen approach on D-PHI scaffold properties, demonstrating an increase in the total scaffold porosity and pore interconnectivity. Specifically, it was found that the use of 10 wt% polyethylene glycol and 65 wt% sodium bicarbonate porogens resulted in a porous (79±3%) D-PHI scaffold with the mechanical properties (elastic modulus=0.16±0.03 MPa, elongation-at-yield=31±5%, and tensile strength=0.04±0.01 MPa) required to withstand the physiologically-relevant cyclic mechanical strain (CMS) that is experienced by VSMCs in vivo. Furthermore, the effects of uniaxial CMS (10% strain, 1 Hz, 4 weeks) on human coronary artery smooth muscle cells (hCASMCs), which were cultured in a porous D-PHI scaffold, were studied using a customized bioreactor. Four weeks of CMS was shown to yield greater DNA mass, more cell area coverage, a better distribution of cells within the scaffold, the maintenance of contractile protein expression and the improvement of tensile mechanical properties. The in vitro and in vivo degradation as well as the in vivo biocompatibility of D-PHI scaffolds were also investigated. Following their subcutaneous implantation in rats (100 days), porous D-PHI scaffolds demonstrated more cell/tissue infiltration within their pores and degraded in a controlled manner and at a faster rate when compared to in vitro studies (120 days), retaining the mechanical integrity required during neo-tissue formation. This thesis provides significant insight into the role of the D-PHI scaffold in combination with physiologically-relevant CMS in modulating VSMC proliferation and phenotype. The findings of this work can be used to tailor vascular tissue regeneration by regulating VSMC function in a directed manner.
Multiple Antenna Broadcast Channels with Random Channel Side Information
Keywords: Broadcast Channels
Precoding
Noisy Channel Side Information

The performance of multiple input single output (MISO) broadcast channels is strongly dependent on the availability of channel side information (CSI) at the transmitter. In many practical systems, CSI may be available to the transmitter only in a corrupted and incomplete form. It is natural to assume that the flaws in the CSI are random and can be represented by a probability distribution over the channel. This work is concerned with two key issues concerning MISO broadcast systems with random CSI: performance analysis and system design. First, the impact of noisy channel information on system performance is investigated. A simple model is formulated where the channel is Rayleigh fading, the CSI is corrupted by additive white Gaussian noise and a zero forcing precoder is formed by the noisy CSI. Detailed analysis of the ergodic rate and outage probability of the system is given. Particular attention is given to system behavior at asymptotically high SNR. Next, a method to construct precoders in a manner that accounts for the uncertainty in the channel information is developed. A framework is introduced that allows one to quantify the tradeoff between the risk (due to the CSI randomness) that is associated with a precoder and the resulting transmission rate. Using ideas from modern portfolio theory, the risk-rate problem is modified to a tractable mean-variance optimization problem. Thus, we give a method that allows one to efficiently find a good precoder in the risk-rate sense. The technique is quite general and applies to a wide range of CSI probability distributions.
Second Messenger-mediated Regulation of Autophagy
Keywords: Autophagy
Second Messenger
Diacylglycerol
cyclic AMP

Autophagy is an evolutionarily conserved degradative eukaryotic cell pathway that plays a role in multiple cellular processes. One important function is as a key component of the cellular immune response to invading microbes. Autophagy has been found to directly target and degrade multiple intracellular bacterial species. In this thesis, I identify and characterize two distinct regulatory mechanisms for this pathway involving the second messengers: diacylglycerol and cyclic adenosine monophosphate (cAMP). Salmonella enteric serovar Typhimurium (S. Typhimurium) is a Gram-negative bacterial species that has been shown to be intracellularly targeted for degradation by autophagy. While targeting of this species has been previously shown to involve ubiquitination, this pathway accounts for only half of targeted bacteria. Here I show that ubiquitin-independent autophagy of S. Typhimurium requires the lipid second messenger diacylglycerol. Diacylglycerol localization to the bacteria precedes autophagy and functions as a signal to recruit the delta isoform of protein kinase C (PKC) in order to promote the specific autophagy of tagged bacteria. Furthermore, I have found that the role of diacylglycerol and PKC delta is not limited to antibacterial autophagy but also functions in rapamycin-induced autophagy indicating a general role for these components in this process. Multiple bacterial species have been found to be targeted by autophagy and while some have developed strategies that allow them to avoid targeting, no bacterial factor has yet been identified that is able to inhibit the initiation of this process. Here I show that two bacterial species, Bacillus anthracis and Vibrio cholera inhibit autophagy through the elevation of intracellular cAMP and activation of protein kinase A. Using two different bacterial cAMP-elevating toxins, I show that multiple types of autophagy are inhibited in the presence of these toxins. This is indicative of a general inhibitory function for these toxins and identifies a novel bacterial defence strategy. This work characterizes both a novel regulatory signal for the induction of autophagy and identifies a novel bacterial tactic to inhibit this process. Together the data presented in this thesis provide novel insight into the regulation of autophagy and offer potential targets for modulation of this process.
Business Models and Incentives in Rating Markets: Three Essays
Keywords: Rating
Strategy
Information Disclosure
Credit
Business Model
Incentives
Rating Agency

This dissertation consists of three essays linking the business models of rating agencies to the rating decisions these agencies make as market intermediaries between buyers and sellers. The first study examines the link between a rating agency‟s primary revenue source and its rating decisions. Theoretically, rating payments could influence rating agency decisions or be counterbalanced by reputational rewards for rating accuracy. I explore this relationship in U.S. corporate credit ratings, where some agencies are primarily paid by bond issuers (sellers) and others by investors (buyers). Analysis of a balanced panel of 338 companies rated between 2005 and 2009 reveals that agencies produce differing ratings consistent with the preferences of their paying customers. Changes in buyer-paid ratings are more frequent and generally precede corresponding seller-paid rating changes. Seller-paid ratings are slower to incorporate negative information, particularly for rated firms in the financial services sector and firms with ratings above a critical grading cutoff. The second study complements the first by estimating the gap between the rating information disclosed by sellers and the information sought by buyers, again using evidence from U.S. corporate credit ratings. While seller willingness to pay for an additional rating is highly concentrated among a subset of relatively high-quality firms, buyers demonstrate more uniform interest in additional ratings for firms at all quality levels. This finding highlights an information gap among high-risk firms that is not a major focus of existing regulation. The third study focuses on rating decisions by government rating agencies, an alternative rating model to those examined in the first two studies. The empirical setting is Canadian film classification where the existence of multiple regional regulators has been justified by claims of variation in community standards. I find significant and increasing consistency in the regulatory decisions of these agencies, suggesting institutional isomorphism that brings into question the persistence of the parallel regional structure. Overall, these studies provide new empirical insight into the relevance of rating agency heterogeneity to firm strategy and policy. The findings may also be relevant to a variety of other settings involving information disclosure such as environmental impact and corporate social responsibility.