VictorJuiz/thesis huggingface dataset:
Fundamental Limits on Low-Latency Sequential Packet Communication
Keywords: Erasure Coding
Low-Latency
Streaming

This thesis explores delay-constrained communication of packets generated sequentially. In the first part of the thesis, we study an established streaming setting, where packets are generated sequentially, transmitted through a network which may introduce packet erasures, and must be decoded by the destination within a strict delay constraint, without feedback. We review the literature on codes for this setting, focusing on the three-node setting in Fong et al., where a relay aids the transmission of the packets. In this relayed setting, a concept denoted as delay spectrum plays a major role. We present novel fundamental limits on this delay spectrum, and then show that, by using these results, we can construct codes for more general settings, such as a multi-access network, where two users transmit their messages to a common destination through a common relay. We further consider a multi-cast setting, where a source wishes to transmit its message to multiple destinations through a common relay, which requires the construction of streaming codes that are able to recover from different numbers of erasures with different delays. We then consider relay adaptation, where the relay changes its coding strategy based on the erasure pattern it observes, and show that adaptation increases the capacity of streaming codes. Finally, we consider a multi-path network and apply ideas developed in the previous settings to construct a code that is tested experimentally, and demonstrate that there are gains to be achieved in audio quality or rate. In the second part of the thesis, we consider a setting where feedback is available, however, with a non-negligible latency, and the channel is modeled as a Markov process that introduces erasures. We still wish to achieve low latency, while also minimizing resources used. We first consider a single-packet transmission, and show that this setting is equivalent to a Partially Observable Markov Decision Process. Motivated by this, we employ reinforcement learning to obtain a good transmission strategy that exploits the channel memory, and compare it to a lower bound. We then test this agent in a streaming setting and show that it outperforms a baseline transmission schedule.
Ustašism as Ideology and Practice: Mass Violence and Genocide in Vukovar District, Croatia, 1939-1945
Keywords: Genocide against Serbs
Holocaust
Independent State of Croatia
Ustaša movement
Ustašism ideology
World War II in Yugoslavia

This dissertation analyzes the ideology of the Ustaša movement and its practice in the Independent State of Croatia (Nezavisna Država Hrvatska, NDH) under the Ustaša regimeduring World War II. Using a case study of the town of Vukovar, this study connects ideas with on-the-ground violence, identifying vectors of ideological dissemination into local communities. In terms of sources, this history makes special use of printed primary sources—books, pamphlets, and newspapers—which were dissected for ideological content, contemporary documents, and postwar testimonies, which provided information on practices and experiences of violence. Rooted in Croat right-wing nationalist tradition, Ustašism claimed as its foundation the thought of nineteenth-century intellectual Ante Starčević, whose ideas served as the prism through which Croat right-wing nationalism, including Ustašism, conceptualized key parameters of the Croat national project. Once in power, the regime implemented Ustašism’s mandates into Croatia’s socio-political arrangements and priorities, employing the media and a broad front of state-controlled organizations. To enforce the nation as the paramount value, the regime resorted to limitless violence, which it used as a concrete, on-the-ground method to hammer Ustašism into local communities. Ustašist principles governed Ustaša population policy. The regime used mass killings and deportations to remove the population it judged incompatible with “new Croatia”: primarily Jews, Roma, and Serb elites as carriers of the Serb national project in the NDH. The majority of the Serb population, mostly peasant non-elites, the regime erased as “Serbs” from NDH’s population categories and subjected to “double conversion”: religious conversion to Catholicism or Croatian Orthodoxy and bureaucratic conversion to Croat ethnonationality. Ustašism’s historical narrative considered these people “Croats-of-old,” whom “foreign elements” had manipulated into Serb identity. The regime also launched a campaign of violent repression of those it identified as Croat national “renegades.” Like in Jews, Roma, and Serb elites, in Croat “renegades” Ustašism recognized “internal enemies,” who carried the stigma of racial-ethnonational “foreignness” and inferiority. Furthermore, even as the regime and its local activists controlled the ideological agenda, ordinary people like “citizen Croat,” the anonymous author of a threatening note, appropriated its logic, threatening to open ideological horizons beyond the regime’s grip.
Advanced Imaging Techniques for Studying Drosophila Cardiogenesis
Keywords: Cardiogenesis
Drosophila
Light sheet
Super resolution

In vertebrates and invertebrates alike, the heart forms as two groups of cells migrate collectively to form a tube. While the genetics of heart development are largely understood, the mechanisms that coordinate cell movements during early cardiac morphogenesis are still unclear. The fruit fly Drosophila melanogaster constitutes an excellent system to investigate the mechanisms of cardiovascular development and disease. Drosophila provides an inexpensive and genetically-tractable in vivo system, features that have been exploited to elucidate the genetics of embryonic heart development. In addition, the Drosophila embryo is transparent, and thus amenable to time-lapse fluorescence microscopy, and is easy to manipulate with biophysical and pharmacological tools. The initial events of heart formation are conserved from fruit flies to humans, including the migration of cardiac precursors to form a primordial tube. Here, I introduce a comprehensive toolkit for the quantitative live imaging of heart development in Drosophila embryos. Using these tools, I found that the cytoskeletal protein actin forms a supracellular cable at the interface between the cardiac progenitors (cardioblasts) and a group of support cells that accompany cardioblasts in their migration (pericardial cells). Biophysical and pharmacological manipulations showed that the cable sustains tension and contributes to the coordination of cardioblast migration. In addition, I applied a tissue morphometrics pipeline that I developed to quantify the dynamics of heart development, and I found that the actin cable does not act as a bowstring to propel cardioblast migration. Taken together, the tools that I have created provide an open-source solution for studying heart development.
Development and Clinical Trranslation of a New Handheld Imaging System for 5-ALA-induced Fluorescence-guided Breast Conserving Surgery
Keywords: breast cancer
fluorescence
medical device
surgical imaging
tissue phantom

During breast conserving surgery (BCS), visualization of cancer remains challenging; the BCS reoperation rate is reported to be 20-70% of patients. An urgent clinical need exists for real-time intraoperative visualization of breast carcinomas during BCS. The ability of a first-generation prototype imaging device to identify breast carcinoma in excised surgical specimens following 5-aminolevulinic acid (5-ALA) administration was previously demonstrated. 5-ALA is a prodrug that induces red fluorescence in tumours. However, this prototype device was not designed to image the surgical cavity for carcinoma remaining after the removal of the lumpectomy. To address this issue, a new handheld fluorescence imaging device called Eagle was developed to improve upon the shortcomings of the first-generation prototype. The Eagle device was designed to image excised specimens and within the surgical cavity. A clinical trial involving 17 patients was conducted to assess the device’s clinical utility. Patients received a 20 mg/kg dose of 5-ALA before imaging, which caused cancerous tissue to appear red in contrast to the green connective tissues and orange-brown adipose tissues when imaged with the Eagle device. The device was able to detect ductal carcinoma in situ (DCIS) at a <1 mm depth that was missed during the standard surgical procedure. Image artifacts due to ambient light, extraneous sources of fluorescence, illumination, and blood within the surgical cavity were also discovered, and potential mitigations have been proposed. A tissue phantom model was developed to further evaluate the device’s imaging sensitivity and identify areas for improvement. The device’s imaging sensitivity was measured using the phantom model. It was found that imaging sensitivity was improved when imaging red tumour-surrogate fluorophores against a healthy breast adipose tissue background than a connective tissue background, suggesting that decreasing the luminance of connective tissues as detected by the Eagle device may improve sensitivity. This thesis resulted in the development of the Eagle imaging system and demonstrated the clinical translation of the technology using a new phantom model. Intraoperative detection of a positive margin with the Eagle device was shown, indicating the potential of this imaging technology to reduce BCS re-excisions.
Communication-efficient Second-order Optimization Methods on Modern Parallel Systems
Keywords: Cloud Computing
Deep Learning
High Performance Computing
Machine Learning
Optimization

The cost of an algorithm on modern computing platforms depends both on the computation and "communication". Communication in a general sense is defined as the data movement among levels of a memory hierarchy or between processors. On modern computer architectures, the communication costis often orders of magnitude larger than the computation cost and this gap is rapidly increasing. This suggests that for the best performance the algorithms should reduce the communication even at the cost of increased computations. The need to automatically process big data has driven the rapid development and deployment of machine learning algorithms. Machine learning applicationsrequire some form of mathematical optimization to find the best parameters obtained by optimizing some objective function representing the machine learning problem. Second-order optimization methods accelerate the optimization process by capturing the geometry of the optimization landscape. However, they can be very time-consuming as they suffer from significant computation and communication overheads. This work presents techniques and algorithms to accelerate second-order optimization methods on modern computing platforms. The performance of second-order methods such as quasi-Newtons and natural gradient descent is improved on modern computing systems. The sub-sampled quasi-Newton method is accelerated on distributed memory systems and demonstrates speedups of up to 12x compared to current efficient implementations. We develop, for the first time, a distributed quasi-Newton algorithm that can achieve local superlinear convergence that uses asynchronous communications to reduce communication overheads. We develop a novel framework for implementing asynchronous communication models on cloud systems that allows practitioners to implement and dispatch asynchronous optimization methods. A scalable natural gradient descent method is developed that computes the curvature information efficiently and reduces the training of deep neural networks up to 2.1x on modern graphical processing units.
Addressing the Realities of Violent Conflict and Mass Violence through the Curriculum: A Comparative Analysis of Secondary Teachers’ Didactic-curricular Development and Implementation Praxes in Two Canadian Provinces
Keywords: Education Leadership
Education Policy
Peace Studies
Policy Formulation
Policy Implementation
Teacher Agency

The purpose of this comparative, qualitative study was to probe and theorise how secondary teachers’ agency contributed to a curriculum that made historical and contemporary events of violent conflict and mass violence the explicit object of analysis in their classrooms in Ontario and Alberta, and how that positive agency was achieved in particular settings and conditions. Positive agency is defined as teachers’ “creative responses to what they perceive as the constraints or inadequacy of formal curriculum policy” (Bascia et al, 2014: 232).Data from this research suggest that the teachers in this project were highly involved and creative in getting the job done, despite policy complexities and spatial (or material) realms within which they operated, the multidimensionality of their relationships to school stakeholders, and the contextual nature of their actions and gatekeeping. The research sharpens our sense of how teachers, who have traditionally been framed as simply implementors of curriculum created by others, actively navigate and shape policy in their situated settings in sophisticated ways in order to accomplish what they seek out to do. In doing so, my dissertation posits that teachers’ positive agency can be a vital part of the policy process. The analyses illustrate how teachers’ approaches to teaching about violence were adjusted, in real time, to meet students’ emotional and epistemological frameworks regarding the processes, causes, and consequences for particular pedagogical purposes. They illustrate how the teachers adapted, extended, and even transcended written curriculum policy documents in relation to the subject of violence, both individually and by collaborating with expert guest speakers. Lastly, they highlight how various school stakeholders, notably parents and principals, figured into teachers’ curriculum development and implementation, in order to provide a sense of how politicised teachers’ roles may be when shaping the vision, substance, and path of a curriculum that critically analyses and problematizes violence. Overall, this study’s aim is first and foremost to illustrate how teachers’ positive agency contributed to a curriculum that addressed violent conflict and mass violent events and processes, drawing attention, in the process, to the factors that enabled or constrained their ability to manifest and achieve their goals.
Subcutaneous Delivery of Allogeneic Islets for Long-Term Engraftment
Keywords: Biomaterials
Immunomodulation
Transplantation
Type I diabetes
Vascularization

Cell replacement therapies offer a treatment for currently incurable diseases like type I diabetes (T1D), an autoimmune disease that results in the destruction of insulin-producing β-cells. However, the immune response to these therapeutic cells remains a significant obstacle for these treatments. Current β-cell replacement therapies rely on portal vein infusion of donor-derived islets making them vulnerable to the instant blood mediated inflammatory reaction (IBMIR). An alternative site is the subcutaneous space which has a large transplant volume, minimal invasiveness, and graft retrievability. However, its native vasculature is insufficient for islet transplantation preventing its use. The Sefton lab has sufficiently vascularized this space to deliver islets to immune-compromised animals using methacrylic acid (MAA)-based biomaterials which have shown angiogenic ability in various forms such as beads, coatings, and hydrogels. To take advantage of MAA for its translative use in subcutaneous cell therapies for immune-competent models, the unique, immune microenvironment of the transplant site had to first be understood. This work therefore characterizes the immune landscape of the MAA-induced, prevascularized subcutaneous space in immune-competent mice with the goal of leveraging this site for allogeneic islet transplantation. We show that the MAA coating generated more vasculature and recruited less immune cells than its uncoated silastic control. Subsequently, the immune response to allogeneic islets in the space was analyzed to identify appropriate cellular targets for allogeneic islet engraftment; allogeneic islets successfully engrafted upon specific depletion of neutrophils, but not with other combinations of commonly used immunosuppressants revealing a need for neutrophil-focused immunosuppression for cell transplantation into the subcutaneous space. Finally, this work explored local immunomodulatory methods to avoid the side effects associated with systemic immunosuppression. Recognizing the critical role of timing and duration in determining immune cell fates, we also explored external triggers for spatiotemporal controlled release. Using ultrasound, we tuned the release of liposomal cargo from hydrogels and showed that these parameters were not harmful to islets. This work contributes to the advancement of subcutaneous cell transplantation by identifying and targeting a critical immune cell for successful allogeneic islet engraftment, and by revealing the potential to use transcutaneous triggers for drug release increasing the attractiveness of the subcutaneous space as a transplantation site.
Synthesis of Small Carbocycles using C1-Bisnucleophiles
Keywords: Carbocycles
Cyclobutane
Cyclopropane
Organic Chemistry
Organic Synthesis
Small Rings

This thesis describes novel methods for the synthesis of 3- and 4-membered carbocycles using C1-bisnucleophiles. These approaches represent new strategies for the formation of functionalized cyclopropanes and cyclobutanes, which are of interest to the chemistry community due to their unique bonding and reactivity. Chapter 1 provides a general introduction to the structure, bonding, and synthesis of cyclopropanes and cyclobutanes. Chapter 2 details the synthesis of cyclopropylamines from alpha-chloroaldehydes and bis(iodozincio)methane via a homoenolate intermediate, wherein solvent composition plays an important role in reaction diastereoselectivity. Chapter 3 describes the synthesis of borylated cyclobutanols via formal [3+1]-cycloaddition of 1,1-diborylalkanes and epihalohydrins or epoxy alcohol derivatives. Derivatization studies are included to demonstrate the utility of the borylated cyclobutanol products and divergent mechanisms for alkyl-/non- and aryl-substituted 1,1-diborylalkanes are presented. Chapter 4 outlines the highly diastereoselective synthesis of borylated (aminomethyl)cyclopropanes using 1,1-diborylalkanes and alpha-bromo or alpha-tosyl aziridines, thereby furthering our understanding of how 1,1-diborylalkanes react with nitrogen-based electrophiles. Computational studies and a mechanistic proposal are outlined and used to rationalize a unique relationship between aziridine stereochemistry and reaction diastereoselectivity. Derivatization studies are also explored. Chapter 5 includes concluding remarks and an outlook for future developments in this area.
Investigations on the Effects of Co-solvents and Hydrostatic Pressure on the Thermal Stability of Guanine-quadruplex DNA
Keywords: Circular dichroism
Dimethyl sulfoxide
G-quadruplex DNA
Hydrostatic pressure
Melting temperature
Stabilization by urea

Guanine-quadruplexes (GQs) are a non-canonical tetra-helical DNA structure formed in solutions containing certain monovalent cations. These structures form spontaneously in solution by the planar association of four guanines around a central cation, such as potassium or sodium, and the subsequent stacking of these tetrads. GQ DNA may be promising targets for drug design and bio-nanotechnology applications owing to their structural diversity and physical properties, and therefore an understanding of the physical and chemical factors that modulate the stability of these GQs is essential. In this thesis, I investigated using circular dichroism and ultraviolet spectroscopy, through a basic research approach, the effects of co-solvents and hydrostatic pressure on the thermodynamic stability of GQs. The co-solvents dimethyl sulfoxide (DMSO) and urea were shown to have opposing effects on the melting temperature, Tm (an indicator of thermodynamic stability); generally, DMSO stabilized and urea destabilized GQs. In a surprising finding, the addition of molar concentrations of the denaturant urea was found to enhance the stability of the G3T GQ, a GQ considered to be one of the most stable nucleic acid structures in existence. Additional work is required to understand the mechanistic effect of DMSO and urea on GQ stability, and how these co-solvents affect the hydration of GQs. I also characterized the volume of the loop component of GQ DNA, and showed through high pressure volume work that the loops are the primary contributor to the change in volume (ΔV) arising from the folding of oligodeoxyribonucleotides to GQs. The next step to support our hypothesis is to determine the volume of the guanine tetrad region. Both the co-solvent and volume data probe the interactions of water molecules around the GQ, which is crucial in understanding the energetics of any biomolecule in solution. These findings are therefore not only important for the characterization of GQ DNA in various cellular and laboratory environments, but also for furthering our understanding of the fundamental forces that enable life to exist.
Self-supervised Scene Representation Using Structured Representations for Surgical Applications
Keywords: Computer Vision
Deep Learning
Graphs
Healthcare
Machine Learning
Surgery

The domain of Computer Vision has recently seen dramatic progress in several applications, including image classification, image segmentation, novel view synthesis, and visual scene understanding, to name a few. Motivated by these advancements, we explore various learning schemes for comprehensive visual scene understanding of dynamic scenes. We assess the efficacy of our approach in the domain of laparoscopic surgery, which has seen limited progress despite the exponential growth of deep learning approaches over the last decade. This can mostly be attributed to factors such as limited datasets, privacy concerns, and the expense of procuring annotations. We hypothesize that the self-supervised learning of these scenes is incredibly important in taking the next-step towards effective generalizable scene understanding. We propose various algorithms for transfer learning and self-supervised novel view synthesis to disassemble the scene into its constituent components. We also discuss the efficacy of these algorithms in complex domains such as laparoscopic surgery, particularly surgical skill analysis. We also delve into the potential of visual scene understanding for surgical skill assessment by leveraging the power of GNNs, we extract meaningful features and offer interpretable results, establishing new benchmarks on multiple datasets. This showcases the effectiveness of GNNs in enhancing scene understanding and accurately predicting surgical skills, once a complex dynamic scene is decomposed. Overall, this study presents novel methodologies for generating structured representations, advancing novel view synthesis, enriching visual scene understanding, and enabling objective evaluation of surgical skills. These groundbreaking advancements mark a transformative milestone in surgical education and feedback, fostering improved surgical outcomes and elevating the standard of patient care.