VictorJuiz/thesis huggingface dataset:
Building More Expressive Structured Models
Keywords: Machine Learning

Structured data and structured problems are common in machine learning, and they appear in many applications from computer vision, natural language understanding, information retrieval, computational biology, and many more. Compared to unstructured problems, where the input data is represented as a vector of independent feature values and output is a scalar prediction like a class label or regression value, both the input and output for structured problems may be objects with internal structure, like sequences, grids, trees or general graphs. Effectively exploiting the structure in the problems can help build efficient prediction models that significantly improve performance. The complexity of the structures requires expressive models that have enough representation capabilities. However, increased model complexity usually leads to increased inference complexity. A key challenge in building more expressive structured models is therefore to balance the model complexity and inference complexity, and explore models that are both expressive enough and have efficient inference. In this thesis, I present our work in the direction of building more expressive structured models, from developing more expressive structured output models, to semi-supervised learning of structured models, and then structured neural network models. The first technical part of the thesis describes a model that uses a new family of expressive high order pattern potentials, for which we characterized the theoretical properties and developed efficient inference and learning algorithms. Next we study semi-supervised learning algorithms for structured prediction problems that can help improve prediction performance by using unlabeled data. Motivated by our observation that standard structured models with iterative inference algorithms can be converted to neural networks, we study in particular structured neural network models for structured problems, and propose a new model that can handle prediction problems on graphs. Discussions about promising future directions are presented at the end of each technical chapter as well as at the end of the thesis.
Thermodynamic Analyses of G-Quadruplexes Formed by DNA Molecules Containing Four Repeats of the Human Telomeric Sequence
Keywords: G-Quadruplex
Human Telomere
Thermodynamics
Volumetrics

Oligodeoxyribonucleotides (ODNs) that are rich in guanines can form four stranded DNA structures known as G-quadruplexes (G4s). G4s are stabilized by physiological concentrations of sodium or potassium cations. The human telomere contains tandem repeats of DNA units that are rich in guanines. HTel is an ODN containing four human telomeric repeats with the sequence [d(AGGGTTAGGGTTAGGGTTAGGG)]. It can adopt various intramolecular G4 topologies depending on the type of stabilizing cation and form G4 aggregates at high DNA concentrations. Our studies focused on the biophysical characterization of the G4s formed by HTel. We demonstrated that the aggregation of G4s is independent of the interactions between the non-guanine residues. The aggregation correlates with the thermodynamic stability of the intramolecular G4. We proposed that the partial unfolding of the intramolecular G4 is critical to the aggregation. The factors that contribute to the formation of the G4 aggregate has been under debate. Here we provide important evidence for a novel mechanism of the aggregate formation: the partial unfolding of the intramolecular G4s. The different intramolecular G-quadruplexes conformations are associated with distinct properties. We next conducted an in-depth analysis of the contributions of purines and pyrimidines in the loops of G4s formed by HTel on their structural and thermodynamic properties. We found here that the stacking interactions provided by purines and the rotational freedom of the pyrimidines have compensatory effects on the stability. In addition to providing support to our previous study, the data here has important implications in the design of small molecules that target the human telomere. Finally, we provided volumetric and hydrodynamic properties of the G-quadruplexes formed by HTel. Despite extensive research in the thermodynamic properties of these G4s, little research has been conducted for their volumetric characterization. Here, we investigated the volumetric changes arising from the formation of G4s. We found here that the magnitude of the change in molar volume during the formation of G4 arises from the differential hydraÂŹtion of the DNA molecule and the creation of water-inaccessible cavities. The sequence of the loops can affect the structure of the G4 and consequently their hydration and molar volumes.
A microfluidic model for in vitro studies of thromboembolism and thrombolysis
Keywords: artificial blood clots
artificial blood vessels
Microfluidics
Soft Materials
Thromboembolism
Thrombolysis

Thromboembolism originates from obstruction of blood vessels with pathological emboli. It is a primary reason for ischemic strokes, pulmonary embolism and myocardial infarction. The correlation between occlusive clot structure, mechanical properties and its resistance to lysis remains unexplored. This thesis describes the development of a microfluidic platform for in vitro studies of thromboembolism and thrombolysis. A â double-modelingâ approach was developed to investigate the motion of an artificial embolus (a hydrogel microparticle) through an artificial blood vessel (a constriction-based microchannel with a circular cross-section). A pressure-driven microfluidic platform was established using agarose hydrogel particles (microgels). We explored the entrance of a microgel into a constriction with a tapered region and water loss by the confined microgel. By studying the behavior of agarose microgels with various dimensions and mechanical properties in narrow microchannels with varying geometries, we established universal principles governing the flow of microgels under spatial constraints. The observed principles agreed excellently with a theoretical model developed for bi-axially deformed microgel. We also showed a non-monotonic change in the flow rate of liquid through the occlusive microgel, which was governed by its progressive confinement in the tapered region of the channel. The developed platform was extended to fibrin microgels, in order to delineate the relationship between the composition, dimensions, and mechanical properties of fibrin hydrogels with respect to their occlusive behavior, relaxation after release from confinement and their ability to lyse. For the same strain experienced in the constriction, soft fibrin microgels with thicker fibers exhibited stronger irreversible deformation, compared to microgels with a denser network structure. Moreover, the former gels are more prone to liquid permeation and fibrinolysis. Lastly, we fabricated bifurcating microchannels with a nearly circular cross-section over multiple generations of sizes. Occlusive fibrin microgels caused redistribution of liquid within the network, thus mimicking blood-perfusion abnormalities in pulmonary embolism.
Design and Synthesis of Self-Assembled Polymeric Nanoparticles for Cancer Drug Delivery
Keywords: Cancer
Drug Delivery
Micelle
Nanoparticle
Polymer

Current chemotherapeutics are plagued by poor solubility and selectivity, requiring toxic excipients in formulations and causing a number of dose limiting side effects. Nanoparticle delivery has emerged as a strategy to more effectively deliver chemotherapeutics to the tumour site. Specifically, polymeric micelles enable the solubilization of hydrophobic small molecule drugs within the core and mitigate the necessity of excipients. Notwithstanding the significant progress made in polymeric micelle delivery, translation is limited by poor stability and low drug loading. In this work, a rational design approach is used to chemically modify poly(D,L-lactide-co-2-methyl-2-carboxytrimethylene carbonate)-graft-poly(ethylene glycol) (P(LA-co-TMCC)-g-PEG) in order to overcome these limitations and effectively deliver drug to tumours. The PEG density of the polymer system was optimized to enhance the stability of our polymeric micelles. Higher PEG densities permitted the lyophilization of micelles and enhanced the serum stability of the system. To increase the drug loading of our system, we facilitated specific intermolecular interactions within the micelle core. For drugs that form colloidal aggregates, such as pentyl-PABC doxazolidine, polymers were used to stabilize the colloidal core against aggregation and protein adsorption. For more challenging molecules, where self-assembly cannot be controlled, such as docetaxel, we modified the polymeric backbone with a peptide from the binding site of the drug to achieve loadings five times higher than those achieved in conventional micelle systems. This novel docetaxel nanoparticle was assessed in vivo in an orthotopic mouse model of breast cancer, where it showed a wider therapeutic index than the conventional ethanolic polysorbate 80 formulation. The improved tolerability of this formulation enabled higher dosing regimens and led to heightened efficacy and survival in this mouse model. Combined, these studies validated P(LA-co-TMCC)-g-PEG nanoparticles as an effective delivery vehicle for two chemotherapeutics, and presents approaches amenable to the delivery of many other clinically relevant hydrophobic drugs or drug combinations.
Online and Continuous Electrocardiogram (ECG) Biometric System
Keywords: Artificial Intelligence
Electrocardiogram
Local Binary Patterns
Machine Learing
Pattern Recognition

Online and continuous biometric system revolves around continuously monitoring identity of subjects using biometrics while using current and past observations only. Electrocardiogram (ECG) signal is prone to noise interference and is a slow signal to acquire. First, we developed an online abnormal electrocardiogram heartbeat detection and removal using one-class Gaussian mixture model of two components. This outlier removal method was implemented in a biometric system and was examined on a 1,012 fingertip acquired ECG signals database. The biometric system had an equal error rate (EER) of 5.94% in comparison to 12.30% in a state-of-the-art approach. Due to eliminating noisy heartbeats, the system may suffer from data imbalance problem, and for that we proposed a method to synthesize data. Data synthesis was based on the assumption that ECG heartbeats exhibit a multivariate normal distribution. When small sample size dataset was simulated and examined in a biometric system, EER of 6.71% was achieved in comparison to 9.35% to the same system but without data synthesis. It was desired to increase biometric system robustness and design a continuous authentication system; hence, a novel feature extraction and a unique continuous authentication strategy were proposed. One-Dimensional Multi-Resolution Local Binary Patterns (1DMRLBP), an online feature extraction for one-dimensional signals was designed, and it was incorporated with sequential sampling to establish a continuous authentication system. This system adaptively updated decision thresholds and sample size during run-time. 1DMRLBP accounts for observations' temporal changes and has a mechanism to extract one feature vector that represents multiple observations. 1DMRLBP also accounts for quantization error, tolerates noise, and extracts local and global signal morphology. When 1DMRLBP was applied on the 1,012 fingertip single session subjects database, an EER of 7.89% was achieved in comparison to 12.30% to a state-of-the-art work. Also, an EER of 10.10% was resulted when 1DMRLBP was applied to the 82 multiple sessions database. Experiments showed that using 1DMRLBP improved EER by 15% when compared to a biometric system that was based on raw time-samples. Lastly, when 1DMRLBP was implemented with sequential sampling to achieve a continuous authentication system, 0.39% false rejection rate and 1.57% false acceptance rate were achieved.
Towards a Perceptual Image Quality Assessment Framework for Color Data
Keywords: color image
distortion
feature extraction
image quality
visual perception

Quality assessment of image data plays a vital role in various applications, e.g., the evaluation and optimization of visual processing algorithms and the monitoring of visual communication systems. Although subjective assessment is the most reliable means to measure image quality, it is not always feasible in practical applications. Therefore, objective image quality metrics (IQMs) that can accurately predict the subjective judgments of average human observers have gained considerable attentions from research community. In the past few decades, numerous IQMs have been proposed to estimate the perceived quality of visual data. Depending on the availability of a reference (i.e., perfect quality) image to compare with, they can be categorized into full-reference (FR) and no-reference (NR) IQMs. Most existing IQMs are designed to rely on image features in the grayscale domain. Despite their reasonable performance in dealing with traditional distortions (e.g. additive white Gaussian noise or Gaussian blur), such grayscale IQMs tend to underestimate the visual disturbance caused by chromatic distortions, e.g., degradation caused from color gamut mapping or tone mapping algorithms. This study proposes new color IQMs capable of handling image data exhibiting both chromatic and achromatic distortions by incorporating perceptual color attributes, e.g., hue and chroma. Both FR and NR IQMs are introduced for different target applications. In particular, the proposed solutions properly process directional hue data using directional statistical tools, addressing the general limitation of existing approaches that treating hue data as linear data. Extensive validation performed on large-scale databases demonstrates the proposed IQMs correlate well with the subjective ratings over commonly encountered chromatic and achromatic distortions, indicating that the appropriate handling of highly informative hue data improves the prediction accuracy of color IQMs. These promising results indicate that they can be deployed on a wide range of color image processing problems as generalized quality assessment solutions.
Ubiquitin Engineering: Understanding Ubiquitin Recognition and Generating Affinity Reagents
Keywords: Alternative Scaffolds
Phage Display
Protein Engineering
Saturation Scanning
Ubiquitin

Protein-protein interactions are necessary for virtually all biological processes. There have been tremendous efforts to document the diversity of molecular recognition, and to understand how molecular recognition occurs. The understanding of molecular interaction has also served as the foundation for designing novel protein interactions for use in therapeutics, diagnostics and basic sciences. An attractive system for studying protein-protein interactions is the ubiquitin (Ub) system. Ub is a protein modifier that is combinatorially ligated onto substrate proteins to influence substrate turnover and function. Ub uses a common surface to interact with more than 1000 proteins and plays pivotal roles in cell physiology. Despite the substantial structural information on Ub mediated interactions, there is no clear understanding of how individual Ub residues contribute to Ubâ s broad scope of interactions. To address this question, I used affinity enhanced Ub variants (Ubvs) as proxies of native Ub in saturation scanning. Using saturation scanning, I studied the interactions between Ubvs and two Ub specific proteases (USP), USP2 and USP21, and elucidated a common functional epitope that is critical for USP recognition. The functional epitope recognizes USP residues that are conserved among the human USP family, suggesting it may make functional contributions in many other USP interactions. While the functional epitopes for Ub binding to USP2 and USP21 share many identical residues, there exist distinct clusters of residues that are responsible for gaining high affinity and specificity to either USP2 or USP21. In this thesis, I also describe the usage of Ub as an alternative scaffold for generating affinity reagents. I developed a novel Ub phage library for the generation of Ubvs to targets of interest. I present validation data on Ubvs selected to bind mammalian cell surface receptor, Her3, and an intracellular protein, Grb2, showing that Ubvs can be used like conventional antibodies in cell biological experiments and can be utilized to antagonize cell signaling within a cell. My work demonstrates that protein-engineering approaches can reveal novel aspects of Ub biology and generate novel affinity reagents to probe intracellular signaling pathways.
The Other Averroes: Revealed Law and the Craft of Juristic Disagreement
Keywords: Averroes / Ibn Rushd
Islamic law
juristic disagreement
khilaf

The role of Abū l-Walīd Ibn Rushd (d. 595/1198) in the Western Medieval intellectual tradition has been well documented. Of equal recognition is the prevalent interest in his philosophy which has dominated his study in the West since the earliest attempts at translating his commentaries into Latin less than twenty years after he died. In this dissertation, I explore a significant, though less familiar, side of Ibn Rushd’s intellectual life; namely, his legal writings. Through a systematic and topical approach, I develop an in-depth study of his Bidāyat al-Mujtahid (The Jurist’s Primer). I investigate his method of legal analysis and synthesis and pay special attention to his account of the causes of juristic disagreement (asbāb al-khilāf). I argue that the Bidāya is a unique work with which Ibn Rushd sought to substantiate what he, as a young scholar, had envisioned to be the best model of engaging revealed law for legal practice; a model that cuts across different schools’ legal hermeneutics and reconciles jurists’ disagreements to establish legal unity within legal diversity. I conclude that Ibn Rushd was a scholar of imposing height in law, just as he was in philosophy, and his Bidāyat al-Mujtahid is a rich source for several practical views on issues relevant to our time, therefore, it deserves more scholarly attention.
Predictors of Influenza among Individuals 60 years and Older
Keywords: Clinical symptoms
Influenza
Older adults

Accurate and timely identification of influenza in older adult patients is important for the appropriate use of additional precautions and antiviral treatment. Clinical characteristics helpful for symptom-based diagnosis of influenza among older adults are unclear. We aimed to identify factors predictive of influenza among individuals aged > 60 years and derive a clinical decision rule for influenza among older adult patients. In the first part of the thesis, we conducted a meta-analysis on factors associated with influenza in older adults. Based on pooled estimates, we identified multiple symptoms associated with seasonal influenza but with low to moderate sensitivity and/or specificity. For the commonly studied symptom complex, fever and cough, the predictive performance was lower in older adults as compared to younger adults. Few studies explored the usefulness of epidemiological factors for the prediction of influenza. An observational study on predictors of influenza among older adults presenting to the emergency department was conducted for two influenza seasons. We recruited and interviewed patients, and tested them for influenza. Current influenza-like illness definitions were inadequate for capturing influenza in older adults. The clinical predictors of influenza in older adults were similar to predictors previously identified in younger adults. A lower triage temperature to define 'fever' was more useful in capturing influenza cases in older adults, and the association between cough and disease increased with advancing age. We derived a clinical decision rule for the diagnosis of influenza among older adults. We developed a score-based model that stratified patients into low, moderate and high risk categories. The best performing model consisted of three variables: feverishness, cough and widespread influenza activity according to FluWatch/Google Flu Trends. Our results suggest that, as in younger adults, the key predictors of influenza in older adults were fever and cough. However, older adults require a lower threshold for measured fever and including both measured fever and feverishness prior to medical assessment is helpful. The presence of cough may need to be elicited among older adult patients. Our decision rule requires validation, but may provide a mechanism for emergency departments to more efficiently use laboratory testing and more promptly administer antivirals.
Principal's Instructional Leadership: Leading Capacity for Learning
Keywords: Development
Leadership
Principal
Professional

Over the past decades, a body of literature on the instructional role of the principal has emerged (Hallinger , 1996). In our times of educational reforms and attempts at closing achievement gaps, the positive influence of the school principal as capacity builder has been gathering much interest (Bredeson, 2003; Davies, 2009; DuFour, 1991; DuFour, DuFour Eaker, 2008; Leithwood, K., Seashore-Lewis, Anderson, S. Wahlstrom, K., 2004;Venables, 2011). But if Liethwood et al. (2004) argue that the principal's influence on student achievement comes second only to the teacher's influence, much of how such influence is exerted within school communities remains to be uncovered. The conceptual framework from the study is inspired by Timperley and Alton-Lee's (2008) iterative cycle of teacher professional development, where teacher professional development is followed by changing teaching practices which in turn, is informed by student outcomes. The present conceptual framework has adapted the model to include the school principal. The purpose of this study was to gain a better understanding of the principal's leadership role as it pertains to the role's reality as a school capacity builder, asking the question: How do school principals influence the professional development of teachers to support teachers' instructional practices for student learning? The study attempted to answer the following three sub questions: 1) How do principals perceive their role in influencing the professional development of their teachers? 2) What are the strategies employed by principals to support teachers' professional development? 3) What are the barriers to supporting teachers' professional learning and growth that school leaders face daily? Semi-structured interviews were conducted with fourteen principals, 10 elementary and four secondary. All principals were from publicly-funded school boards in the province of Ontario, Canada. Main impediments to building school capacity include the principals' continuous struggle between administrative and leadership duties, the lack of autonomy in the planning of professional development, the lack of time for follow ups and the centralized nature of boards' professional development plans. Implications for policy, practice and future research are discussed.