VictorJuiz/thesis huggingface dataset:
District Influence on Principals' Efficacy and Sensemaking in their School Improvement Efforts

Part of a larger study of high-performing districts in Ontario, this mixed method (qualitative and quantitative) study identified school district actions perceived by principals to help them make sense of their leadership work and contribute to their sense of efficacy in carrying out that work. Qualitative data included interviews with 23 principals, 10 senior district leaders, and 5 trustees in two high-performing districts in the province. Narrative analysis was used to analyze these data. Quantitative data were provided by the responses of 1,563 principals and 250 senior district leaders to two forms of a survey which included sub-sets of questions about variables of special interest to this study. Descriptive statistics were used to summarize the survey results. Interview results showed that in the two study districts, each of 12 district actions framing the study were perceived to influence principals’ efficacy or principals’ sensemaking or both. Of those 12 district actions, principals in one of the two study districts identified 8 of the 12 district actions as especially influential in helping them to make sense of their work and to develop their sense of efficacy for carrying out that work; 10 of the 12 district actions were identified by principals in the second study district. Four of the 12 district actions were common across the responses of principals in both study districts including: networking interactions among principals; job-embedded and regional professional development opportunities; support from superintendents with the writing of school improvement plans; and emphasis and support with data interpretation and use for decision making processes. Except for one of these four district actions (use of evidence for decision making), survey results pointed to the same sets of district actions as particularly influential to both principals’ efficacy and sensemaking. This research adds to the understanding of what districts do that helps their school leaders work more effectively. Implications are identified for the actions of district leaders and for future research.

Keywords: District Actions, District Influences, Principal's Sensemaking, Principal's Efficacy, Instructional Leadership, Principal's Leadership Practices
Advisor: Leithwood, Kenneth
Anionic Nitrogen Chelate Ligands: From Molecular Self-assembly to Small Molecule Activation

This thesis examines the use of anionic nitrogen chelate ligands in coordination-driven self-assembly and small molecule activation. The two classes of anionic nitrogen chelate ligands that were explored are β-diiminate and 4,5-diazafluorenide derivatives. Chapter 2 deals with Pd β-diiminate chemistry. Chloro-bridged dimers served as versatile starting materials, and their reactivity toward pyridine and arylboronic acids was explored. An unusual transmetallation reaction with arylboronic acids triggered the self-assembly of tetrapallada-macrocycles. The formation of the self-assembled tetrapallada-macrocycles is through the generation of new Pd-C bonds. Chapter 3 deals with 4,5-diazafluorenide as an actor ligand in CO2 activation. A reversible formal insertion of CO2 into a remote ligand C-H bond was discovered. A variety of spectator metal centres were used to tune the reactivity of the actor ligand toward CO2. The spectator metal centre could even be replaced entirely with an organic group allowing for the first metal-free reversible tandem CO2 and C-H activation. Chapter 4 deals with the reactivity of dinuclear Rh 4,5-diazafluorenide-9-carboxylate complexes with dihydrogen in an attempt to reduce the trapped CO2 moiety. A series of stepwise stoichiometric reactions with H2, NMR experiments at low temperatures with added PPh3 or CO2, along with 13C-labelling experiments were conducted in an attempt to identify the products of this reaction and gain some mechanistic insight. Chapter 5 deals with using ambidentate 4,5-diazafluorene derivatives to synthesize linkage isomers, heterobimetallic complexes, and self-assembled macrocycles. The synthesis a new ligand family, 3,6-substituted 4,5-diazafluorene ligands is presented, along with coordination chemistry towards a {RuCp*}+ fragment. Finally in Chapter 6 the coordination chemistry of 3,6-diaryl substituted 4,5-diazafluorene derivatives was explored with the goal of generating low-coordinate species for the activation of small molecules, especially N2. The synthesis of the first trialkylborohydride complex of vanadium is presented.

Keywords: Small Molecule Activation
Chelate Ligands
Self-Assembly
Advisor: Song, Datong
Inferring Genetic Regulatory Networks Using Cost-based Abduction and Its Relation to Bayesian Inference

Inferring Genetic Regulatory Networks (GRN) from multiple data sources is a fundamental problem in computational biology. Computational models for GRN range from simple Boolean networks to stochastic differential equations. To successfully model GRN, a computational method has to be scalable and capable of integrating different biological data sources effectively and homogeneously. In this thesis, we introduce a novel method to model GRN using Cost-Based Abduction (CBA) and study the relation between CBA and Bayesian inference. CBA is an important AI formalism for reasoning under uncertainty that can integrate different biological data sources effectively. We use three different yeast genome data sources—protein-DNA, protein-protein, and knock-out data—to build a skeleton (unannotated) graph which acts as a theory to build a CBA system. The Least Cost Proof (LCP) for the CBA system fully annotates the skeleton graph to represent the learned GRN. Our results show that CBA is a promising tool in computational biology in general and in GRN modeling in particular because CBA knowledge representation can intrinsically implement the AND/OR logic in GRN while enforcing cis-regulatory logic constraints effectively, allowing the method to operate on a genome-wide scale.Besides allowing us to successfully learn yeast pathways such as the pheromone pathway, our method is scalable enough to analyze the full yeast genome in a single CBA instance, without sub-networking. The scalability power of our method comes from the fact that our CBA model size grows in a quadratic, rather than exponential, manner with respect to data size and path length. We also introduce a new algorithm to convert CBA into an equivalent binary linear program that computes the exact LCP for the CBA system, thus reaching the optimal solution. Our work establishes a framework to solve Bayesian networks using integer linear programming and high order recurrent neural networks through CBA as an intermediate representation.

Keywords: Genetic Regulatory Networks
Cost-Based Abduction
Bayesian Network
Systems biology
recurrent neural network
Maximum a Posteriori Assignment
reasoning under uncertainty
Advisor: Bonner, Anthony
Zhang, Zhaolei
The Immigrant Experience, Child Feeding and Care: An Examination of the Determinants of Children's Health and Nutrition in Newcomer Families

This study aims to examine how the migration experience influences newcomer mothers’ young child feeding and care practices and their children’s overall health. The thesis comprises three separate manuscripts, each of which examines one of the three intermediate determinants of the nutritional status of young children (UNICEF 1990): access to healthcare, household food insecurity, and child feeding and care practices. The research was conducted in Toronto’s Jane-Finch neighbourhood, a suburban neighbourhood home to a high density of newcomers. Thirty-two participants (16 Sri Lankan Tamil and 16 Latin American) who had migrated to Canada within the past five years as refugee claimants or family sponsored immigrants participated in the study. Data collection consisted of semi-structured interviews with women from low-income households who had a child between the ages of 1 and 5 years. Spanish and Tamil speaking interviewers interviewed each participant two or three times. Data was analyzed using a mid-level approach in which broad analytical themes are determined prior to analysis and specific themes were then generated based on participants’ perspectives and are grounded in the data. The first manuscript examines newcomer mothers’ experiences accessing physicians for their children and identifies the major gaps between mothers’ expectations and their actual experiences that lead to barriers in communication and overall patient dissatisfaction. The second manuscript demonstrates that mothers’ past experiences with food insecurity affect two aspects of the construct of food insecurity: its managed aspect and its temporal nature. This finding has implications for the measurement of food insecurity in newcomer populations. The third manuscript reveals that newcomer mothers are exposed to several parallel and often conflicting systems of knowledge concerning health and nutrition for their children, and that their utilization of Canada’s Food Guide is impeded by its failure to acknowledge alternate parallel knowledge systems. These findings can be applied to the development of social and health policy aimed at improving cultural competency in healthcare and nutrition education and at ameliorating the income constraints leading to household food insecurity.

Keywords: Household food insecurity
Immigrant Health
Child Health
Canada's Food Guide
Migration
Healthcare access
Advisor: Sellen, Daniel
Estimation of Volumetric Breast Density from Digital Mammograms

Mammographic breast density (MBD) is a strong risk factor for developing breast cancer. MBD is typically estimated by manually selecting the area occupied by the dense tissue on a mammogram. There is interest in measuring the volume of dense tissue, or volumetric breast density (VBD), as it could potentially be a stronger risk factor. This dissertation presents and validates an algorithm to measure the VBD from digital mammograms. The algorithm is based on an empirical calibration of the mammography system, supplemented by physical modeling of x-ray imaging that includes the effects of beam polychromaticity, scattered radation, anti-scatter grid and detector glare. It also includes a method to estimate the compressed breast thickness as a function of the compression force, and a method to estimate the thickness of the breast outside of the compressed region. The algorithm was tested on 26 simulated mammograms obtained from computed tomography images, themselves deformed to mimic the effects of compression. This allowed the determination of the baseline accuracy of the algorithm. The algorithm was also used on 55 087 clinical digital mammograms, which allowed for the determination of the general characteristics of VBD and breast volume, as well as their variation as a function of age and time. The algorithm was also validated against a set of 80 magnetic resonance images, and compared against the area method on 2688 images. A preliminary study comparing association of breast cancer risk with VBD and MBD was also performed, indicating that VBD is a stronger risk factor. The algorithm was found to be accurate, generating quantitative density measurements rapidly and automatically. It can be extended to any digital mammography system, provided that the compression thickness of the breast can be determined accurately.

Keywords: Medical Physics
Radiology
Breast Cancer
Breast Density
Epidemiology
Quantitative Imaging
Advisor: Yaffe, Martin
A Randomized Controlled Trial Evaluating Lanolin for the Treatment of Nipple Pain Among Breastfeeding Women

It is widely accepted that breast milk is the optimal source of infant nutrition. Despite the World Health Organization (WHO) recommendation of exclusive breastfeeding for the first 6 months of infant life, many women discontinue breastfeeding as a result of perceived difficulties. Nipple pain is a highly prevalent, significant reason for breastfeeding cessation. Among the numerous interventions for nipple pain, the application of lanolin is commonly recommended, with endorsement by Health Canada, The La Leche League, and International Board Certified Lactation Consultants. The few studies that have evaluated the effectiveness of lanolin on nipple pain have lacked methodologic rigor, and are thus not reliable or generalizable. As such, the purpose of this trial was to rigourously evaluate the effect of lanolin for the treatment of nipple pain among breastfeeding women. This single-site randomized controlled trial (RCT) compared the application of lanolin (treatment) to usual postpartum care (not applying lanolin) for the treatment of nipple pain. The primary outcome for this trial was the effect on pain severity, as measured by a numeric rating scale (NRS) at 4 days post-randomization. Of 186 participants, 93 were randomized to the treatment group and 93 to the usual care group. At 4 and 7 days post-randomization there were no statistically significant differences in pain scores between groups. It is noteworthy that by 7 days post-randomization there were clinically relevant decreases in nipple pain in both groups. However, there were no statistically significant differences between groups for other outcomes, including pain measured with the short-form McGill Pain Questionnaire, breastfeeding duration, breastfeeding exclusivity, and breastfeeding self-efficacy. Despite these findings, women in the treatment group were significantly more satisfied receiving lanolin for their nipple pain than those receiving usual care. Since the use of lanolin is no more effective than applying nothing to the nipples for the management of nipple pain, the widespread use of lanolin is questionable. Further research is required on the role of interventions to prevent nipple pain and damage, and the effect of anticipatory guidance on improving breastfeeding outcomes for those experiencing nipple pain in the early postpartum period.

Keywords: nipple pain
randomized controlled trial
breastfeeding
Advisor: Dennis, Cindy-Lee
Modulation of N-Methyl-D-Asparate Receptor by Transient Receptor Potential Melastatin Type-2 Regulates Neuronal Vulnerability to Ischemic Cell Death

Neuronal vulnerability to ischemia is dependent on the balance between pro-survival and pro-death cellular signaling. In the latter, it is increasingly appreciated that toxic Ca2+ influx can occur not only via postsynaptic glutamate receptors, but also through other cation conductances. One such conductance, the Transient receptor potential melastatin type-2 (TRPM2) channel, is a non-specific cation channel having similar homology to TRPM7, a conductance reported to play a key role in anoxic neuronal death. The role of TRPM2 conductances in ischemic Ca2+ influx has been difficult to study due to the lack of specific modulators. Here we used TRPM2-null mice (TRPM2(-/-)) to study how TRPM2 may modulate neuronal vulnerability to ischemia. TRPM2(-/-) mice subjected to transient middle cerebral artery occlusion (tMCAO) exhibited smaller infarcts when compared to wild-type (WT) animals, suggesting the absence of TRPM2 to be protective. Surprisingly, field potentials (fEPSPs) recorded during oxidative stress in brain slices taken from TRPM2(-/-) mice revealed increased excitability, a phenomenon normally associated with ischemic vulnerability, whereas WT fEPSPs were unaffected. The upregulation in fEPSP in TRPM2(-/-) neurons was blocked selectively by an NR2A antagonist. This oxidative stress-induced increase in excitability of TRPM2(-/-) fEPSPs depended on the upregulation and downregulation of NR2A and NR2B-containing NMDARs, respectively, and augmented pro-survival signaling via Akt and ERK pathways culminating in the inhibition of the proapoptotic factor, GSK3β. Cultured hippocampal neurons from TRPM2(-/-) animals subjected to oxygen glucose deprivation had a reduction in cell death in comparison to WT neurons, demonstrating that absence of TRPM2 is protective at the neuronal level in vitro. Our results suggest that TRPM2 plays a role in downregulating pro-survival signals in central neurons and that TRPM2 channels may comprise a therapeutic target for preventing ischemic damage.

Keywords: ischemia
TRPM2 NMDA
Advisor: Tymianski, Michael
Syllabification and Phrasing in Three Dialects of Sudanese Arabic

This study is a synchronic derivational analysis of phonological phenomena in three dialects of Sudanese Arabic. Its main goal is to provide a unified prosodic account of syncope and of the phonological processes functioning as strategies of repairing unsyllabified segments in the dialects of Urban Central Sudanese Arabic, Shukriiya, and Hamar. The domains of these processes are argued to follow from the degree of restriction that dialects place on word-level and phrase-level syllabification. To this end, the study proposes an analysis of syllabification in the three dialects that identifies the degree to which word-level syllabification is exhaustive, the segments that may be marked extrasyllabic and the conditions regulating their extrasyllabic status, the phrasal level at which these segments must be syllabified, and the level at which alteration to syllable structure is disallowed. In identifying the degrees of restriction dialects place on syllabification and resyllabification, the analysis provides a principled explanation for the levels of repair of unsyllabified segments as well as the domains of syncope. The study also provides an analysis of word stress and an analysis of phonological phrase formation. By revealing and accounting for the interesting phonological patterns attested in these dialects, the study aims to contribute to the area of Arabic phonology in general and to research on the typology of Arabic dialects in particular. In addition to the analyses proposed, its substantial contribution in this regard is a significant body of original data that is being analysed for the first time. With respect to dialects of Sudanese Arabic, the study represents a new direction of enquiry, one that seeks to disentangle their respective grammars and reveal the interesting ways in which they pattern alike and diverge.

Keywords: Arabic Phonology
Sudanese Arabic
Syllabification
Phrasal Syllabification in Arabic
Prosodic domains of syllabification
Prosodic domains of syncope and epenthesis
Repairing Unsyllabified segments
Sudanese Arabic Stress
Advisor: Dresher, Elan
The Registration and Segmentation of Heterogeneous Laser Scanning Data

Light Detection And Ranging (LiDAR) mapping has been emerging over the past few years as a mainstream tool for the dense acquisition of three dimensional point data. Besides the conventional mapping missions, LiDAR systems have proven to be very useful for a wide spectrum of applications such as forestry, structural deformation analysis, urban mapping, and reverse engineering. The wide application scope of LiDAR lead to the development of many laser scanning technologies that are mountable on multiple platforms (i.e., airborne, mobile terrestrial, and tripod mounted), this caused variations in the characteristics and quality of the generated point clouds. As a result of the increased popularity and diversity of laser scanners, one should address the heterogeneous LiDAR data post processing (i.e., registration and segmentation) problems adequately. Current LiDAR integration techniques do not take into account the varying nature of laser scans originating from various platforms. In this dissertation, the author proposes a methodology designed particularly for the registration and segmentation of heterogeneous LiDAR data. A data characterization and filtering step is proposed to populate the points’ attributes and remove non-planar LiDAR points. Then, a modified version of the Iterative Closest Point (ICP), denoted by the Iterative Closest Projected Point (ICPP) is designed for the registration of heterogeneous scans to remove any misalignments between overlapping strips. Next, a region-growing-based heterogeneous segmentation algorithm is developed to ensure the proper extraction of planar segments from the point clouds. Validation experiments show that the proposed heterogeneous registration can successfully align airborne and terrestrial datasets despite the great differences in their point density and their noise level. In addition, similar testes have been conducted to examine the heterogeneous segmentation and it is shown that one is able to identify common planar features in airborne and terrestrial data without resampling or manipulating the data in any way. The work presented in this dissertation provides a framework for the registration and segmentation of airborne and terrestrial laser scans which has a positive impact on the completeness of the scanned feature. Therefore, the derived products from these point clouds have higher accuracy as seen in the full manuscript.

Keywords: LiDAR
Heterogeneous
Registration
Segmentation
Advisor: McCabe, Brenda
Habib, Ayman
High Performance Soft Processor Architectures for Applications with Irregular Data- and Instruction-level Parallelism

Embedded systems based on FPGAs frequently incorporate soft processors. The prevalence of soft processors in embedded systems is due to their flexibility and adaptability to the application. However, soft processors provide moderate performance compared to hard cores and custom logic, hence faster performing soft processors are desirable. Many soft processor architectures have been studied in the past including Vector processors and VLIWs. These architectures focus on regular applications in which it is possible to extract data and/or instruction level parallelism offline. However, applications with irregular parallelism only benefit marginally from such architectures. Targeting such applications, we investigate superscalar, out-of-order, and Runahead execution on FPGAs. Although these architectures have been investigated in the ASIC world, they have not been studied thoroughly for FPGA implementations. We start by investigating the challenges of implementing a typical inorder pipeline on FPGAs and propose effective solutions to shorten the processor critical path. We then show that superscalar processing is undesirable on FPGAs as it leads to low clock frequency and high area cost due to wide datapaths. Accordingly, we focus on investigating and proposing FPGA-friendly OoO and Runahead soft processors. We propose FPGA-friendly alternatives for various mechanisms and components used in OoO execution. We introduce CFC, a novel copy-free checkpointing which exploits FPGA block RAMs for fast and dense storage. Using CFC, we propose an FPGA-friendly register renamer and investigate the design and implementation of instruction schedulers on FPGAs. We then investigate Runahead execution and introduce NCOR, an FPGA-friendly non-blocking cache tailored for FPGAs. NCOR removes CAM-based structures used in conventional designs and achieves the high clock frequency of 278 MHz. Finally, we introduce SPREX, a complete Runahead soft core incorporating CFC and NCOR. Compared to Nios~II, SPREX provides as much as 38% higher performance for applications with irregular data-level parallelism with minimal area overhead.

Keywords: FPGA
Soft Core
Architecture
High Performance
Advisor: Moshovos, Andreas