VictorJuiz/thesis huggingface dataset:
Longitudinal Patterning of Structured Light and its Applications in Sensing
Keywords: Electromagnetic Waves
Fourier Optics
Holography
Laser Beam Shaping
Nondiffracting Beams
Structured Light

Recent advances in laser beam shaping using tools such as Spatial Light Modulators (SLMs) or phase plates has made it possible to engineer various properties of light in a sophisticated manner, thus opening many new possibilities in Structured Light. In particular, much attention has been dedicated to engineering the properties of non-diffracting light beams, mainly due to their long depth-of-field and self-healing behavior. Notably, controlling the intensity profile of non-diffracting beams has led to many advances in optical tweezers, micro-manipulation, and atom guiding. In addition to intensity, beams with helical phase fronts have been constructed such that they carry Orbital Angular Momentum (OAM); a conserved degree-of-freedom that can be transferred to micro-particles or deployed as means of optical communications. Furthermore, the wavelength and state of polarization are two additional properties of light that play a decisive role in applications such as materials processing, microscopy, and optical communications. While much effort has been dedicated to structuring the aforementioned properties of non-diffracting light beams ― namely its intensity, OAM, polarization, and wavelength ― at a single 2D plane, controlling such properties at multiple planes along the beam's axis has scantly been investigated. In this dissertation, we establish a systematic method to design, create, and analyze a new generation of non-diffracting Structured Light beams in which various properties of light can be controlled, separately or simultaneously, along the beam's longitudinal axis of propagation. This includes longitudinal control over the intensity profile, OAM, polarization, wavelength, and even the propagation trajectory of the beam (almost at-will); thus creating a new optical toolkit with many degrees-of-freedom to meet the rising demand for advanced Structured Light. In addition, we report on unusual physical phenomena; for instance, one in which the OAM of light can be reversed/changed locally without violating any conservation laws. Finally, we show that Longitudinally Structured Light can be exploited to measure the index of refraction of fluids; providing high resolution measurements over a wide dynamic range, and thus solving an old trade-off that has hitherto been untackled in refractive index sensing.
Mixing Monte Carlo and Partial Differential Equation Methods For Multi-dimensional Optimal Stopping Problems Under Stochastic Volatility
Keywords: Monte-Carlo
Optimal Stopping Problems
Partial Differential Equations
Stochastic Volatility

In this thesis, we develop a numerical approach for solving multi-dimensional optimal stopping problems (OSPs) under stochastic volatility (SV) that combines least squares Monte Carlo (LSMC) with partial differential equation (PDE) techniques. The algorithm provides dimensional reduction from the PDE and regression perspective along with variance and dimensional reduction from the MC perspective. In Chapter 2, we begin by laying the mathematical foundation of mixed MC-PDE techniques for OSPs. Next, we show the basic mechanics of the algorithm and, under certain mild assumptions, prove it converges almost surely. We apply the algorithm to the one dimensional Heston model and demonstrate that the hybrid algorithm outperforms traditional LSMC techniques in terms of both estimating prices and optimal exercise boundaries (OEBs). In Chapter 3 we describe methods for reducing the complexity and run time of the algorithm along with techniques for computing sensitivities. To reduce the complexity, we apply two methods: clustering via sufficient statistics and multi-level Monte Carlo (mlMC)/multi-grids. While the clustering method allows us to reduce computational run times by a third for high dimensional problems, mlMC provides an order of magnitude reduction in complexity. To compute sensitivities, we employ a grid based method for derivatives with respect to the asset, S, and an MC method that uses initial dispersions for sensitivities with respect to variance, v. To test our approximations and computation of sensitivities, we revisit the one-dimensional Heston model and find our approximations introduce little-to-no error and that our computation of sensitivities is highly accurate in comparison to standard LSMC. To demonstrate the utility of our new computational techniques, we apply the hybrid algorithm to the multi-dimensional Heston model and show that the algorithm is highly accurate in terms of estimating prices, OEBs, and sensitivities, especially in comparison to standard LSMC. In Chapter 4 we highlight the importance of multi-factor SV models and apply our hybrid algorithm to two specific examples: the Double Heston model and a mean-reverting commodity model with jumps. Again, we were able to obtain low variance estimates of the prices, OEBs, and sensitivities.
Digital Signal Processing for the Canadian Hydrogen Intensity Mapping Experiment
Keywords: CHIME
Correlators
Radio Astronomy
Radio Instrumentation
RFI Mitigation

This thesis presents the design, development, operation, and performance of digital signal processing systems for the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and its Pathfinder. CHIME is designed to investigate the behaviour of Dark Energy in order to constrain its physical mechanism; it will do so by examining the geometry of the recent universe using as a `standard ruler' the imprint of the Baryon Acoustic Oscillation (BAO) feature in the 21 cm emission of neutral Hydrogen. In order to construct the complete set of visibilities for CHIME's 2048 inputs and 400\,MHz of bandwidth, the FX correlator's X-Engine must be capable of ingesting 6 Tib/s of data and completing 8.4×1014 complex multiply-and-accumulate operations per second; these requirements make CHIME's X-Engine by far the largest currently in operation. Using mass-produced Graphics Processing Units (GPUs), commercial off-the-shelf computer hardware, and a sealed-loop liquid-cooling system, the CHIME correlator X-Engine achieves high performance and exceptional efficiency. This thesis presents a detailed description of the X-Engine hardware design and a thorough evaluation of its performance, with additional commentary on aspects of the design and deployment which may warrant additional consideration by those planning similar systems. The substantial computational power available in the correlator system provided an opportunity for pre-integration excision of transient Radio-Frequency Interference (RFI). A number of RFI mitigation techniques were examined, including Median Absolute Deviation and Spectral Kurtosis measures; the latter was implemented on CHIME and the Pathfinder, and results from tests of the RFI detection system are presented. The CHIME Pathfinder, in addition to acting as a test-bed for hardware and analysis techniques, produced an archive of visibility data spanning three years; from this, maps were produced covering the entire northern sky for 609 sidereal days. This thesis details the data processing pipeline which was employed to generate these maps as well as analysis of the resulting data products with regards to their overall variability and the properties of known point-like sources.
Persistent Hypermetabolism after Severe Burn Injury: Effects of Hepatic Stress and Regeneration
Keywords: ER stress
liver
metabolism
mitochondria
stem cell
unfolded protein response

Burn injury represents one of the most severe forms of trauma. Persistent hypermetabolism and inflammatory response are common in major burned patients, contributing to morbidity and mortality. The underlying mechanisms are largely unknown and therefore novel and effective treatments are lacking. Liver is the fundamental mediator of post-burn immunologic and metabolic derangement and significant hepatomegaly is universally present and associated with the persistent hypermetabolism and inflammatory response in severely burned patients. We sought to understand if such a hepatomegaly is the consequence of 1) increased hepatic fat infiltration due to intensified lipolysis in white adipose tissue (WAT) and inter-organ cross-talk between liver and WAT, or 2)aberrant liver regeneration induced by stress response and liver damage which carries on hypermetabolic and pro-inflammatory signaling, contributing to persistent hypermetabolism and inflammatory response after major burn injury. Rodent models of burn plus LPS administration, high fat diet (HFD) plus burn, and 30% TBSA burn of Sox9-cre/ERT2:ROSA26-EYFP mice were used for the studies. In the rat model of burn plus LPS, we demonstrated 1) increased ER stress, inflammasome activation, apoptosis and lipolysis in WAT,contributing to liver steatosis (Chapter 2);2) hepatic ER stress and inflammasome activation, contributing to liver damage and organ dysfunction(Chapter 3). In the mouse model of HFD plus burn, we showed that hepatic fat infiltration and meta-flammation augment the liver damage and metabolic dysfunction post-burn(Chapter 4). We lineage-traced the facultative liver progenitor cells after burn injury and demonstrated that liver regeneration by this group of cells peaked around 2 weeks post-burn. Significant activation of multiple inflammatory and metabolic signaling pathways was indicated by transcriptomic analysis and verified by further analysis in the liver stem cells and their progeny post-burn as compared with both sham and self-renewal mature hepatocytes. Concomitant down-regulation of LXR signaling in the liver stem cells post-burn implicated the therapeutic potential of LXR agonist in ameliorating pro-inflammatory response and restoring lipid homeostasis after major burn injury (Chapter 5). In conclusion, severe burn injury leads to hepatic stress response, liver damage and steatosis, stimulating liver regeneration from facultative stem cells which contributes to persistent hypermetabolism and pro-inflammatory response.
Localization of Heat Shock Proteins HSPA6 (Hsp70B′), HSPA1A (Hsp70-1) and HSPA8 (Hsc70) in Cultured Human Neuronal Cells
Keywords: Differentiated SH-SY5Y human neuronal cells
Heat shock protein
HSPA1A (Hsp70-1)
HSPA6 (Hsp70B′)
HSPA8 (Hsc70)
Mammalian protein disaggregation/refolding machine

Heat shock proteins (Hsps) are protein repair agents that detect and refold misfolded proteins and prevent their aggregation. Accumulation of protein aggregates is a key feature of neurodegenerative diseases. Treatments that showed beneficial effects in current animal models of neurodegenerative diseases have repeatedly failed in human clinical trials. A better understanding of the proteostasis machinery in human cells is required to design more effective therapeutic compounds. HSPA6 (Hsp70B′) is a stress-inducible member of the HSPA (Hsp70) multigene family that is absent in rat and mouse genomes and has been little studied compared to inducible HSPA1A (Hsp70-1), or constitutively expressed HSPA8 (Hsc70). HSPAs are involved in refolding proteins that misfold due to stress or disease. Binding to DNAJ (Hsp40) inhibits aggregation of misfolded proteins until they can be refolded by HSPA, but this machine cannot dissociate aggregated proteins. Recent studies have identified a disaggregase function performed by the mammalian HSPH (Hsp110) family in co-operation with HSPA/DNAJ in vitro. To advance knowledge of the mammalian disaggregation/refolding machine, this thesis investigates localization of HSPA6, HSPA1A, and HSPA8 with other components of the machine following stress in differentiated human neuronal SH-SY5Y cells. Unique targeting of HSPA6 to nuclear perispeckles and differential localization with disaggregation/refolding machine components at the nucleolus compared to HSPA1A or HSPA8 is observed following thermal stress. siRNA knockdown demonstrates that HSPA6 is protective in the neuronal stress response. MG132 proteotoxicity induces HSPA6 which targets the periphery of cytoplasmic protein aggregates with components of the disaggregation/refolding machine and thus may be involved in the response of differentiated neuronal cells to protein aggregation. Constitutively expressed HSPA8 exhibits similar intracellular targeting as inducible HSPA1A and may act as a rapid stress responder in neuronal cells, circumventing the time lag required to upregulate HSPA1A. In cancer cells, elevated levels of Hsps contribute to their ability to resist cell death. The chemotherapeutic agent cisplatin induces components of the disaggregation/refolding machine. Knockdown of HSPA family members enhances the killing effect of cisplatin on human neuroblastoma cells.
Post-translational Regulatory Mechanisms Acting on KLF4 Mediate Pluripotency Exit in Naïve Mouse Embryonic Stem Cells
Keywords: Early embryogenesis
Embryonic stem cells
KLF4
Nuclear export
Pluripotency exit and differentiation
Post translational regulation

Pluripotent embryonic stem (ES) cells have the potential to self-renew and differentiate to generate all adult tissues. Pluripotency is regulated by an interconnected network of transcription factors including OCT4, SOX2, NANOG and KLF4. This transcriptional network is integrated with extracellular signaling pathways regulating pluripotency and differentiation. Mouse ES cells can be maintained in a state known as naïve pluripotency by culture in leukemia inhibitory factor (LIF) and two signaling pathway inhibitors (LIF/2i). A previous study observed that a reduction in Klf4 transcript, due to LIF withdrawal, was the first change in pluripotency gene expression during differentiation. Based on this finding I hypothesized that removal of KLF4 protein from transcriptional network would be required for exit from pluripotency. To investigate this I examined the levels of pluripotency associated transcription factors in the nucleus of ES cells as they exit the pluripotent state. This investigation revealed that a reduction in KLF4 protein levels did not occur immediately following the reduction in Klf4 transcription; instead I identified nuclear export of KLF4 protein was required for the reduction in Klf4 transcription and pluripotency exit. Next, I investigated Klf4 gene and protein regulation and found that LIF/2i maintains Klf4 expression through both transcriptional and post-translational mechanisms. Specifically, KLF4 protein is highly stable in LIF/2i and this stability is maintained by physical interaction with active transcriptional complexes which ensure nuclear anchoring of the KLF4 protein. Surprisingly, KLF4 protein stability is so high (t½ >24 hr) that protein levels change by
Modeling Invasive Processes at the Tumor-Stroma Interface in Vitro Using Gels for Live Analysis of Compartmentalized Environments (GLAnCE)
Keywords: cancer-associated fibroblast
compartmentalized culture
fibroblast activation
in vitro co-culture
tumor invasion
tumor-stroma interface

Engineered tumor tissues carry promise as tools for making unique biological discoveries, as well as for identifying therapeutic opportunities to tackle cancer. This is because, in a field where 2D tissue culture may be exhausting its potential for further discoveries, 3D tumor tissue grown in vitro represents an intermediate step between these simplistic cultures and the exponentially more complex tissues in vivo. As such, it is necessary for in vitro tumor models to capture sufficient complexity, in order to deliver novel insights that are otherwise unattainable; this means incorporating multiple cell types into tissues with 3D geometries that are recapitulative of specific, disease-relevant, in vivo tissue structures. In this work, the interface between tumor tissue and its surrounding stromal space is generated in vitro, as a site of particular significance for tumor growth. This tumor- stroma interface/edge represents an architecturally unstable site, where cancer cells invade adjacent spaces whilst stromal cells infiltrate the tumor mass; both these processes are associated with increased disease aggressiveness and poor prognosis. We here explore the parameters of this cellular exchange in vitro, which is highly dynamic in terms of spatial heterogeneity and over time. By developing a novel culture platform to visualize and quantify tumor expansion, a spatial stratification is made between the phenotypes, and differentiation states, of cancer cells at the invasive edge versus the bulk of the tumor tissue. Expansion of the stromal tissue compartment in the form of fibroblast infiltration is further assessed by correlating infiltration efficiency to fibroblast differentiation status, a relationship which is then explored by altering the infiltrative phenotype. The work presented here demonstrates how complex in vitro tumor tissues can recapitulate the evolving dynamics of a disease-relevant tissue site, thereby giving access to novel mechanistic insights. It further suggests that the parameters of cellular movement within a tissue space are highly informative and can be leveraged to generate more applicable tumor and tissue models and functional readouts, not only for asking biological questions closer to in vivo physiology, but also to assess the impact of phenotype-altering culture treatments, as a first step towards the identification of compounds with therapeutic benefit.
Random Sorting Networks, the Directed Landscape, and Random Polynomials
Keywords: directed landscape
KPZ universality class
last passage percolation
random polynomials
random sorting networks
Young tableau

The first part of this thesis concerns random sorting networks. A sorting network is a shortest path from 12···n to n···21 in the Cayley graph of the symmetric group Sn generated by adjacent transpositions. We prove that in a uniform random n-element sorting network σn, all particle trajectories are close to sine curves with high probability. We also find the weak limit of the time-t permutation matrix measures of sign. As a corollary, we show that if Sn is embedded into Rn via the map τ→(τ(1),τ(2),...τ(n)), then with high probability, σn is close to a great circle on a particular (n-2)-dimensional sphere. These results prove conjectures of Angel, Holroyd, Romik, and Vir'ag. To prove these results, we first find a local limit and prove that local speeds follow an arcsine distribution. The second part of this thesis concerns last passage percolation. The conjectured limit of last passage percolation is a scale-invariant, independent, stationary-increment process with respect to metric composition. We prove this for Brownian last passage percolation. We construct the Airy sheet and characterize it in terms of the Airy line ensemble. We also show that last passage geodesics converge to random Hölder-2/3- continuous functions. To prove these results, we develop a new probabilistic framework for understanding the Airy line ensemble. The third part of this thesis concerns random polynomials. Let Gn = ∑ni=0 ξipi, where the ξi are i.i.d. non-degenerate complex random variables, and {pi} is a sequence of orthonormal polynomials with respect to a regular measure τ supported on a compact set K. We show that the zero measure of Gn converges weakly almost surely to the equilibrium measure of K if and only if Elog(1 + |ξ0|) < ∞, and that the zero measure of Gn converges weakly in probability to the equilibrium measure of K if and only if P(|ξ0| > en) = o(n-1). Our methods also work for more general sequences of asymptotically minimal polynomials in Lp(τ), where p ∈ (0, ∞].
Dynamicity in Speech Perception
Keywords: implicit learning
phonetics
psycholinguistics
speech perception

Human listeners dynamically adjust their perceptual category boundaries and cue weights following brief exposure to idiosyncratic speech (Norris et al., 2003; Idemaru and Holt, 2011). This dissertation presents five experiments, each exploring a different facet of when and how listeners recalibrate. The first three experiments use the classical perceptual learning paradigm, where listeners are exposed to speech exhibiting an idiosyncratic pattern, such as an atypically high VOT boundary between /t/ and /d/, and then tested on whether they adjusted their boundary according to that training. Experiment 1 used weaker evidence to train listeners on the pattern than previous studies, by using word-initial targets in training. Experiment 2 exposed listeners to a more complex pattern than previous studies, by using a second-order (i.e. context-dependent) idiosyncrasy. In both experiments, listeners succeeded at learning. Experiment 3 tested whether listeners make use of phonological category knowledge in learning these patterns. There was no evidence of learning. However, some methodological weaknesses made it difficult to conclude that listeners could not learn this type of pattern; further work is needed to assess this. The last two experiments looked at cue reweighting -- reliance on different acoustic cues to the same contrast. Experiment 4 tested the effects of noise on cue weighting. It confirmed previous work showing that noise affects cue weighting, and expanded beyond previous work in showing that different types of noise affect cue weighting differently. Noise especially suppressed reliance on cues incongruent in periodicity with the noise type, suggesting listeners may be sensitive to spectral characteristics of background noise in adaptive cue reweighting. Experiment 5 was the first test of unsupervised learning of cue reweighting based on exposure. Listeners were exposed to a contrast varying on along two acoustic dimensions where one was a more reliable cue than the other. The results suggested that listeners learned to reweight perceptual cues based on their exposure, supporting the hypothesis that listeners implicitly learn multi-dimensional statistical distributions in speech. Together, these experiments provide new data and contribute novel methodologies to further our understanding of the dynamic nature of adaptation in human speech perception.