VictorJuiz/thesis huggingface dataset:
New Insights into the Regulation of Intestinal Immunity by Nod1 and Nod2
Keywords: Innate Immunity
Th17

Nod1 and Nod2 are intracellular pattern recognition receptors that detect specific moieties of peptidoglycan, a critical component of the bacterial cell wall, to initiate host innate immune responses. Importantly, mutations in the human NOD2 gene have been associated with increased risk to develop mucosal auto-inflammatory disorders such as Crohn’s Disease. However, how Nod1 and Nod2 mediate mucosal homeostasis still remains unclear. In Chapter 2, I determined that mice deficient for both Nod1 and Nod2 (Nod1-/-Nod2-/-) exhibited delayed induction of intestinal inflammation at early timepoints after infection with Citrobacter rodentium compared to wild-type mice, which correlated with compromised control of the pathogen at later timepoints. Notably, I determined that induction of the cytokines IL-17 and IL-22 in the cecal lamina propria (LP) was blunted in Nod1-/-Nod2-/- mice after infection with either C. rodentium or Salmonella enterica serovar Typhimurium. Importantly, I found that Th17 cells were the principal producers of IL-17 and IL-22 after infection. Due to the rapid kinetics of activation and the regulation by Nod1 and Nod2, I termed this early mucosal response the innate Th17 (iTh17) response. The iTh17 cells exhibited an effector memory phenotype and required priming from the enteric microbiota for full induction. Therefore, in Chapter 3, I next determined that major histocompatibility complex (MHC) class II expression in hematopoietic cells was required for the induction of LP Th17 responses after infection. Interestingly, I found that the percentage IL-17+CD8+ T cells was strongly upregulated when MHCII signaling was ablated, suggesting a dynamic compensatory mechanism of IL-17-producing T cell responses in the mucosa. In Chapter 4, I identified MDP(D-Glu2)-OCH3 as a synthetic Nod2 agonist that exhibited increased stimulatory ability of Nod2-dependent NF-B activation compared to MDP in an unbiased screen. Moreover, I determined that MDP(D-Glu2)-OCH3 induced more potent inflammatory responses both in vitro and in vivo and was a better adjuvant than MDP. Together, the data presented in this thesis expand our current understanding of the roles of Nod1 and Nod2 in the intestinal LP, the regulation of IL-17 producing T cells in the gut and the therapeutic potential of novel Nod2 agonists.
Practical Volume-reduction Strategies for Low-power High-frequency Switch Mode Power Supplies
Keywords: Power Electronics
Power Conversion
DC-DC
Integrated Circuit
Switch Mode Power Supply
Digital Control
Mixed-Signal
CMOS
Analog-to-Digital Converter
Load Transient

The miniaturization of dc–dc switch-mode power supplies (SMPS) is of a key importance in volume-sensitive portable devices, such as cell phones, tablet computers, and digital cameras. In these systems, multiple SMPS are required to provide well regulated voltage and power to various electronic components such as the central processing unit (CPU) and random-access memory (RAM). The combined volume, weight, and surface area footprint of these SMPS is usually the largest component. Traditionally, SMPS volume reduction has been achieved through increased switching frequencies; however, for power-sensitive applications this is undesirable due to the increased switching losses. This thesis presents two alternative, power-efficient, SMPS miniaturization methods: one control and one topology based. The presented controller recovers from load transients with virtually minimum possible output voltage deviation, reducing the reactive component size. The controller utilizes a simple algorithm, requiring no knowledge of the converter parameters and virtually no processing power. The simplicity of the control concept enabled the design of an area and power efficient integrated circuit (IC) implementation. The entire IC is implemented in a CMOS 0.18µm process on a 0.26 mm2 silicon area, which is comparable to the state-of-the-art analog solutions. For the experimental system the deviation (output capacitor size) is about four times smaller than that of a fast PID compensator having a 1/10th of the switching frequency bandwidth. The second solution is a complementary converter topology that has a smaller output filter volume, improved dynamic response, and lower switching losses compared to the state-of-the-art solutions. To reduce the volume and switching losses, the input-to-output voltage difference is decreased with a capacitive attenuator that replaces the input filter capacitor and has approximately the same volume. Both the attenuator and the downstream buck converter share the same set of switches, minimizing conduction losses. A single multi-mode digital controller governs operation of both stages, seamlessly regulating the output and input center-tap voltages. Experiments with a 5–1.5-V, 2.5-A, 1-MHz prototype show that, compared to the conventional buck, the merged topology has 43% smaller inductor, 36% smaller output capacitor, up to 30% lower power losses, and a 25% faster transient response.
Computational Prediction of Target Genes of MicroRNAs
Keywords: miRNAs

MicroRNAs (miRNAs) are a class of short (21-25 nt) non-coding endogenous RNAs that mediate the expression of their direct target genes post-transcriptionally. The goal of this thesis is to identify the target genes of miRNAs using computational methods. The most popular computational target prediction methods rely on sequence based determinants to predict targets. However, these determinants are neither sufficient nor necessary to identify functional target sites, and commonly ignore the cellular conditions in which miRNAs interact with their targets \emph{in vivo}. Since miRNAs activity reduces the steady-state abundance of mRNA targets, the main goal of this thesis is to augment large scale gene expression profiles as a supplement to sequence-based computational miRNA target prediction techniques. We develop two computational miRNA target prediction methods: InMiR and BayMiR; in addition, we study the interaction between miRNAs and lncRNAs using long RNA expression data. InMiR is a computational method that predicts the targets of intronic miRNAs based on the expression profiles of their host genes across a large number of datasets. InMiR can also predict which host genes have expression profiles that are good surrogates for those of their intronic miRNAs. Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3 UTRs and are significantly more likely to have predicted Pol II-III promoters in their introns. We also develop BayMiR that scores miRNA-mRNA pairs based on the endogenous footprint of miRNAs on gene expression in a genome-wide scale. BayMiR provides an ``endogenous target repression" index, that identifies the contribution of each miRNA in repressing a target gene in presence of other targeting miRNAs. This thesis also addresses the interactions between miRNAs and lncRNAs. Our analysis on expression abundance of long RNA transcripts (mRNA and lncRNA) shows that the lncRNA target set of some miRNAs have relatively low abundance in the tissues that these miRNAs are highly active. We also found lncRNAs and mRNAs that shared many targeting miRNAs are significantly positively correlated, indicating that these set of highly expressed lncRNAs may act as miRNA sponges to promote mRNA regulation.
Towards the Pedagogy of Risk: Teaching and Learning Risk in the Context of Secondary Mathematics
Keywords: Mathematics Education
Probability Teaching and Learning
Risk Literacy
Understanding of Risk

A qualitative case study was presented in order to explore an inquiry-based learning approach to teaching risk in two different grade 11 mathematics classes in an urban centre in Canada. The first class was in an all-boys independent school (23 boys) and the second class was in a publicly funded religious school (19 girls and 4 boys). The students were given an initial assessment in which they were asked about the safety of nuclear power plants and their knowledge of the Fukushima nuclear power plant accident. Following the initial assessment, the students participated in an activity with the purpose of determining the empirical probability of a nuclear power plant accident based on the authentic data found online. The second activity was then presented in order to determine the impact of a nuclear power plant accident and compare it to a coal power plant accident. The findings provide evidence that the students possess intuitive knowledge that risk of an event should be assessed by both its likelihood and its impact. The study confirms the Levinson et al. (2012) pedagogic model of risk in which individuals’ values and prior experiences together with representations and judgments of probability play a role in the estimation of risk. The study also expands on this model by suggesting that pedagogy of risk should include five components, namely: 1) knowledge, beliefs, and values, 2) judgment of impact, 3) judgment of probability, 4) representations, and 5) estimation of risk. These ii components do not necessarily appear in the instruction or students’ decision making in a chronological order; furthermore, they influence each other. For example, judgments about impact (deciding not to consider accidents with low impact into calculations) may influence the judgments about probability. The implication for mathematics education is that a meaningful instruction about risk should go beyond mathematical representations and reasoning and include other components of the pedagogy of risk. The study also illustrates the importance of reasoning about rational numbers (rates, ratios, and fractions) and their critical interpretation in the pedagogy of risk. Finally, the curricular expectations relevant to the pedagogy of risk from the Ontario secondary curriculum are identified.
The Choice-based Perspective of Choice-of-Law
Keywords: choice-of-law
party autonomy
Kant
Savigny
most significant relationship principle
better-law

This study offers the so-called ”Choice-Based Perspective” of the choice-of-law question or “CBP”. Drawing on the legal philosophy of Immanuel Kant and through careful evaluation of comprehensive theory of Kant’s follower- Friedrich Carl von Savigny, CBP offers a purely private conception of the subject which rejects the conventional wisdom that choice-of-law has to be grounded on the principle of states’ sovereignty. Furthermore, it will be argued that the proposed approach holds much sway in practice, for the normative underpinnings of CBP are already embedded in many traditional and contemporary choice-of-law rules, doctrines, and concepts.
Insights into the Interactions between CFTR and Small Molecule Modulators
Keywords: Cystic Fibrosis
CFTR
phosphorylation

Cystic Fibrosis (CF) is a life-threatening autosomal recessive disease affecting 1:3600 children born in Canada. CF is caused by mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) chloride channel. The most common disease causing mutation is a deletion of residue F508, resulting in a structurally compromised protein which is retained in the endoplasmic reticulum and targeted for proteasomal degradation. Therapeutic strategies currently being pursued to alleviate the afflictions caused by this and other mutants include the use of corrector compounds to modify the surface expression of the channel, and potentiator compounds to increase cAMP-mediated channel activity. Despite the discovery of a number of small molecules affecting CFTR, much is still unknown about the nature of these interactions. This thesis contains the investigation of two potentiators: VRT-532 and VX-770, and two correctors VX-809 and C18. We assessed the consequences of interactions with these drugs on CFTR channel activity, ATPase activity and phosphorylation. We demonstrated that VRT-532 binds directly to mutant CFTR to modify its channel and ATPase activity. VX-770, known to bind directly to CFTR, can stimulate channel activity in the absence of cAMP stimulation in baby hamster kidney (BHK) cells. Correctors VX-809 and C18, based off the same molecular scaffold, are both capable of acutely augmenting cAMP-stimulated channel activity, providing evidence for potentiator activities in these compounds. Quantitative mass spectrometry (MS) techniques demonstrate a defect in phosphorylation at Ser-660 in the regulatory (R) domain in the major mutant. Treatment with C18 was unable to repair this defect. These novel findings regarding interactions between several small molecules and CFTR contributes to the understanding of the mechanism of action of these compounds, and will help identify how they may be modified for greater efficacy to improve the treatment of CF disease.
Rhetorics of Colonialism in Visual Documentation
Keywords: visual
rhetoric
photography
crosscultural
Indigenous
Amerindian
Native
representation

The original face-to-face encounter of American Indians in portraits and pictorial field studies reiterates the encounter between the colonial state, settlers and Indigenous communities. Mechanical reproduction had extended visual technologies creating a revolution in communications which began with the early use of the woodcut (around 1461). A tradition of portraiture from the eighteenth century then re-imagined American Indian peoples for new social and political uses. This dissertation begins by introducing the frontier representations of artists Benjamin West, George Catlin, Paul Kane and William G. R. Hind. Attention then shifts to the collaborative relation between photographer and subject required by the photographic technology of the period. The pictorial contact moment was an interactive communication between photographer and subject. Hence the image-making contact moment is a dialogue, an interchange. Thus the image became a meeting ground where cultural processes were intersubjective and where the present interacted with the past. At the centre of these representations is a two-way looking within a dialogical imagination. As colonial powers expanded and increased control territorially, changes in the dialogic relations were marked in the subject’s presentation of self, the artists’ renditions and the photographer’s aesthetics. Earlier artists like Benjamin West in “The Death of General Wolfe” (1770) used the publishing industry to challenge monologic stereotypes. However, as colonial powers exerted greater repressions, lucrative popular culture industries like the Wild West Shows constituted an imagined frontier which called for several other perspectival approaches: Lakota Chief Red Cloud used the photographic medium for peace activism and community building, Harry Pollard’s photojournalism documented Indigenous communities in Alberta and Edward S. Curtis’s pictorialism became a genre of ethnography in the twenty volume, "The North American Indian". Using a historical framework and interdisciplinary methodologies, this dissertation examines early representations of the North American West in a dialogue as a frontier of difference iterated through technologies of illustration and photography.
A Numerical Methodology for Aerodynamic Shape Optimization in Turbulent Flow Enabling Large Geometric Variation
Keywords: Optimization
Computational Aerodynamics
Numerical Methods
Turbulent Flows

The increase in the availability and power of computational resources over the last fifteen years has contributed to the development of many different types of numerical optimization methods and created a large area of research focussed on numerical aerodynamic shape optimization and, more recently, high-fidelity multidisciplinary optimization. Numerical optimization provides dramatic savings when designing new aerodynamic configurations, as it allows the designer to focus more on the development of a well-posed design problem rather than on performing an exhaustive search of the design space via the traditional cut-and-try approach, which is expensive and time-consuming. It also reduces the dependence on the designer’s experience and intuition, which can potentially lead to more optimal designs. Numerical optimization methods are particularly attractive when designing novel, unconventional aircraft for which the designer has no pre-existing studies or experiences from which to draw; these methods have the potential to discover new designs that might never have been arrived at without optimization. This work presents an extension of an efficient gradient-based numerical aerodynamic shape optimization algorithm to enable optimization in turbulent flow. The algorithm includes an integrated geometry parameterization and mesh movement scheme, an efficient parallel Newton-Krylov-Schur algorithm for solving the Reynolds-Averaged Navier-Stokes (RANS) equations, which are fully coupled with the one-equation Spalart-Allmaras turbulence model, and a discrete-adjoint gradient evaluation. In order to develop an efficient methodology for optimization in turbulent flows, the viscous and turbulent terms in the ii governing equations were linearized by hand. Additionally, a set of mesh refinement tools was introduced in order to obtain both an acceptable control volume mesh and a sufficiently refined computational mesh from an initial coarse mesh. A series of drag minimization studies was carried out which show that the algorithm is able to maintain robustness in the mesh movement and flow analysis in the presence of large shape changes, an important requirement for performing exploratory optimizations aiming to discover novel configurations and for multidisciplinary optimization. Additionally, the algorithm is able to find incremental improvements when given well-designed initial planar and nonplanar geometries. A comparison of Euler-based and RANS-based optimizations highlights the importance of considering viscous and turbulent effects. A multi-point optimization demonstrates that the algorithm is able to address practical aerodynamic design problems.
Pregnancy-related Deaths in India: Causes of Death and the Use of Health Services
Keywords: maternal death
population-health
India

Introduction: The distribution of the causes of maternal deaths, and the impact of facility-based obstetric care access (obstetric access) at the individual and population level in India have not yet been quantified. Objectives: (i) estimate the physician agreement for coding of maternal deaths; (ii) explain the distribution of maternal mortality in India; and (iii) quantify the effect of obstetric access on the probability of maternal death, accounting for effect modification of state level skilled attendant coverage. Methods: I used the nationally representative Million Death Survey (MDS) of the causes of death from 2001-3. I identified context-specific risk factors from the field reports to provide information on care patterns before deaths. The 1096 MDS maternal deaths were matched to 147 001 controls of non-fatal deliveries from a representative fertility survey. Findings: 1.Inter-rater reliability was substantial for two physicians assigning a cause of death. 2. Three-quarters of India's maternal deaths were clustered in rural areas of poorer states, although these regions have only half the estimated births in India. The distribution of major causes of maternal deaths (most notably hemorrhage, obstruction, sepsis, abortion) did not differ between poorer and richer states. Two-thirds of maternal deaths died seeking healthcare, most in a critical medical condition. 3. The probability of maternal death decreased with increasing skilled attendant coverage, among both women who had and had not accessed obstetric care. The risk of death among women who had obstetric access was higher (at 50% coverage, OR=2.32) than among those women who did not. However at higher population levels of coverage of safe birth, obstetric access had no effect. This effect appears to be driven partially by reverse causality, in which critical illness is shown to confound the association between care seeking and death. Conclusions: Simple MDS methods enable measurement of the levels, determinants of maternal deaths. Currently, obstetric access in India appears to be an indicator for inequitable access and poor quality even though it is a life-saving intervention. Reduction in maternal mortality in India will require expanded population-based coverage of skilled birth attendance and improved and early access to high quality obstetric care.
Deep Neural Network Acoustic Models for ASR
Keywords: Deep Neural Networks
Acoustic models
Automatic speech recognition
Machine learning

Automatic speech recognition (ASR) is a key core technology for the information age. ASR systems have evolved from discriminating among isolated digits to recognizing telephone-quality, spontaneous speech, allowing for a growing number of practical applications in various sectors. Nevertheless, there are still serious challenges facing ASR which require major improvement in almost every stage of the speech recognition process. Until very recently, the standard approach to ASR had remained largely unchanged for many years. It used Hidden Markov Models (HMMs) to model the sequential structure of speech signals, with each HMM state using a mixture of diagonal covariance Gaussians (GMM) to model a spectral representation of the sound wave. This thesis describes new acoustic models based on Deep Neural Networks (DNN) that have begun to replace GMMs. For ASR, the deep structure of a DNN as well as its distributed representations allow for better generalization of learned features to new situations, even when only small amounts of training data are available. In addition, DNN acoustic models scale well to large vocabulary tasks significantly improving upon the best previous systems. Different input feature representations are analyzed to determine which one is more suitable for DNN acoustic models. Mel-frequency cepstral coefficients (MFCC) are inferior to log Mel-frequency spectral coefficients (MFSC) which help DNN models marginalize out speaker-specific information while focusing on discriminant phonetic features. Various speaker adaptation techniques are also introduced to further improve DNN performance. Another deep acoustic model based on Convolutional Neural Networks (CNN) is also proposed. Rather than using fully connected hidden layers as in a DNN, a CNN uses a pair of convolutional and pooling layers as building blocks. The convolution operation scans the frequency axis using a learned local spectro-temporal filter while in the pooling layer a maximum operation is applied to the learned features utilizing the smoothness of the input MFSC features to eliminate speaker variations expressed as shifts along the frequency axis in a way similar to vocal tract length normalization (VTLN) techniques. We show that the proposed DNN and CNN acoustic models achieve significant improvements over GMMs on various small and large vocabulary tasks.