VictorJuiz/thesis huggingface dataset:
Holocene Carbon Dynamics in the Patterned Peatlands of the Hudson Bay Lowland, Canada: Reducing Landscape-Scale Uncertainty in a Changing Climate

Northern peatlands have accumulated ~500 Pg of carbon (C) over millennia, and contributed to a net climate cooling. However, the fate of peatland C pools and related climate-system feedbacks remain uncertain under scenarios of a changing climate and enhanced anthropogenic pressure. Here, Holocene C dynamics in the Hudson Bay Lowland, Canada (HBL) are examined at the landscape scale with respect to glacial isostatic adjustment (GIA), climate, and ecohydrology. Results confirm that the timing of peat initiation in the HBL is tightly coupled with GIA, while contemporary climate explains up to half of the spatial distribution of the total C mass. Temporal patterns in C accumulation rates (CARs) are related to peatland age, ecohydrology, and possibly paleoclimate, whereby CARs are greatest for younger, minerotrophic peatlands. Rapid and widespread peatland expansion in the HBL has given rise to a globally significant C pool, in excess of 30 Pg C and two-thirds of which is of late Holocene age. Yet, long-term decomposition of previously accrued peat has potentially resulted in some C losses, especially during the late Holocene when the landscape was occupied by an abundance of minerotrophic peatlands and climate was characterized by more precipitation and similar-to-colder temperatures than present. Model deconstruction of HBL C dynamics indicate that 85% of C losses occurred during the late Holocene, while spatio-temporal scaling of modern methane (CH4) emissions suggest a potential flux of 1 – 7 Pg CH4 to the late Holocene atmosphere, which provides evidence of a peatland contribution to the late Holocene CH4 rise recorded in ice cores. Although HBL peatlands may continue to function as a net C sink, conservative climate scenarios predict warmer and wetter conditions in the next century – beyond the HBL’s range of past climate variability, yet within the peatland climate domain – with implications for primary production and decomposition. Further investigation into controls on spatial-temporal C dynamics may reduce uncertainty concerning the HBL’s potential to remain a net C sink under future climate and resource management scenarios, and contribute to our understanding of global peatland C-climate dynamics.

Keywords: bog
fen
glacial isostatic adjustment
methane
permafrost
radiocarbon
Advisor: Finkelstein, Sarah A
A Multi-temporal Remote Sensing Approach to Freshwater Turtle Conservation

Freshwater turtles are a globally declining taxa, and estimates of population status are not available for many species. Primary causes of decline stem from widespread habitat loss and degradation, and obtaining spatially-explicit information on remaining habitat across a relevant spatial scale has proven challenging. The discipline of remote sensing science has been employed widely in studies of biodiversity conservation, but it has not been utilized as frequently for cryptic, and less vagile species such as turtles, despite their vulnerable status. The work presented in this thesis investigates how multi-temporal remote sensing imagery can contribute key information for building spatially-explicit and temporally dynamic models of habitat and connectivity for the threatened, Blanding’s turtle (Emydoidea blandingii) in southern Ontario, Canada. I began with outlining a methodological approach for delineating freshwater wetlands from high spatial resolution remote sensing imagery, using a geographic object-based image analysis (GEOBIA) approach. This method was applied to three different landscapes in southern Ontario, and across two biologically relevant seasons during the active (non-hibernating) period of Blanding’s turtles. Next, relevant environmental variables associated with turtle presence were extracted from remote sensing imagery, and a boosted regression tree model was developed to predict the probability of occurrence of this species. Finally, I analysed the movement potential for Blanding’s turtles in a disturbed landscape using a combination of approaches. Results indicate that (1) a parsimonious GEOBIA approach to land cover mapping, incorporating texture, spectral indices, and topographic information can map heterogeneous land cover with high accuracy, (2) remote-sensing derived environmental variables can be used to build habitat models with strong predictive power, and (3) connectivity potential is best estimated using a variety of approaches, though accurate estimates across human-altered landscapes is challenging. Overall, this body of work supports the use of remote sensing imagery in species distribution models to strengthen the precision, and power of predictive models, and also draws attention to the need to consider a multi-temporal examination of species habitat requirements.

Keywords: Blanding's turtle
habitat modeling
land cover classification
landscape connectivity
remote sensing
threatened species
Advisor: He, Yuhong
Computational Modeling of Word Learning: The Role of Cognitive Processes

Young children, with no prior knowledge, learn word meanings from a highly noisy and ambiguous input. Moreover, child word learning depends on other cognitive processes such as memory, attention, and categorization. Much research has focused on investigating how children acquire word meanings. A promising approach to study word learning (or any aspect of language acquisition) is computational modeling since it enables a precise implementation of psycholinguistic theories. In this thesis, I investigate the mechanisms involved in word learning through developing a computational model. Previous computational models often do not examine vocabulary development in the context of other cognitive processes. I argue that, to provide a better account of child behavior, we need to consider these processes when modeling word learning. To demonstrate this, I study three phenomena observed in child word learning. First, I show that individual differences in word learning can be captured through modeling the variations in attentional development of learners. Understanding these individual differences is important since although most children are successful word learners, some exhibit substantial delay in word learning and may never reach the normal level of language efficacy. Second, I have studied certain phenomena (such as the spacing effect) where the difficulty of learning conditions results in better retention of word meanings. The results suggest that these phenomena can be captured through the interaction of attentional and forgetting mechanisms in the model. Finally, I have investigated how children, as they gradually learn word meanings, acquire the semantic relations among them. I propose an algorithm that uses the similarity of words in semantic categories and the context of words, to grow a semantic network. The resulting semantic network exhibits the structure and connectivity of adult semantic knowledge. The results in these three areas confirm the effectiveness of computational modeling of cognitive processes in replicating behavioral data in word learning.

Keywords: Cognitive Modeling
Computational Linguistics
Language Acquisition
Advisor: Stevenson, Suzanne
Intersections of Youths' Perceptions: Youths' Perceptions of Their Treatment by the Criminal Justice System and Other Social Institutions

In three studies, I explore the manner in which young people's encounters with the justice system affects their views of the system as whole. Framed within the procedural justice perspective, I examine how adolescents perceive their treatment by criminal justice actors and explore the relationship of these views to their views of other parts of the justice system and to their views of other social institutions (e.g., the education system and employment sector). In this way, this research seeks to examine whether treatment by the justice system matters to young people in the same way that it has been reported to be important for adults. The findings, although somewhat mixed, suggest that treatment does matter to young people, but that the ways in which they understand the police, courts and corrections may differ from the more cohesive or consistent views of adults. Young people appear to be in the process of developing their views of the criminal justice system during adolescence and have not forged generalized views of the criminal justice system as a whole. Rather, they distinguish their experiences and views of the police from those of the courts and corrections. Similarly, young people do not appear to possess a negativity bias to all authority figures and social institutions, with the findings here suggesting that the ways in which young people view their treatment by criminal justice actors and the legitimacy of the criminal justice system are quite different from how they are viewing teachers and the educational system as well as future employment and success in later life. Taken together, the findings point to a more nuanced perspective on the nature of youths' views of the criminal justice system and other civic institutions.

Keywords: Perceptions of the criminal justice system
Young offenders
Youth and courts
Youth and police
Youth justice
Advisor: Doob, Anthony N
Betti Tables of Maximal Cohen-Macaulay Modules over the Cones of Elliptic Normal Curves

Graded Betti numbers are classical invariants of finitely generated modules describing the shape of a minimal free resolution. We show that for maximal Cohen-Macaulay modules over a homogeneous coordinate rings of smooth Calabi-Yau varieties X computation of Betti numbers can be reduced to computations of dimensions of certain Hom groups in the bounded derived category Db(X). In the simplest case of a smooth elliptic curve E we use our formula to get explicit answers for Betti numbers. Description of the automorphism group of the derived category Db( E) in terms of the spherical twist functors of Seidel and Thomas plays a major role in our approach. We study the homogeneous coordinate rings of the embeddings of the elliptic curve E into projective spaces by a complete linear system of degree n > 0. Case n = 3 is the simplest case of a smooth plane cubic. Here we show that there are only four possible shapes of the Betti tables up to a shifts in internal degree (•), and two possible shapes up to a shift in internal degree and taking syzygies. For elliptic normal curves of degree n > 3 recursive formulae for the Betti numbers are given, and possible shapes of the Betti tables are described. Results on the Betti numbers are applied to study Koszul and Ulrich modules over the homogeneous coordinate ring. For n = 1,2 the elliptic curve E is embedded as a hypersurface into a weighted projective space. Homogeneous coordinate rings are known as minimal elliptic singularities E 7 (for n = 2) and E8 (for n = 1). We show that the same approach to Betti numbers works. In fact formulae for the Betti numbers in these cases are even simpler than in the plane cubic case.

Keywords: Betti numbers
elliptic curve
MCM modules
Advisor: Buchweitz, Ragnar-Olaf
Robust Optimization Methods for Breast Cancer Radiation Therapy

The goal of radiation therapy (RT) is to eliminate cancerous cells by directing radiation beams to the hit the cancer target while sparing the surrounding healthy tissue. In breast cancer, the proximity of the heart to the radiation beams often results in the delivery of excessive dose to the heart, leading to a high risk of cardiac complications after the treatment. The heart moves in and out of the radiation beams due to breathing motion which is often irregular and unpredictable. The challenge is to remain within the clinical limits on the volume of the heart receiving a high dose in the presence of breathing motion uncertainty. This thesis investigates robust optimization (RO) methods to minimize the radiation dose to the heart in breast cancer RT. %under breathing motion uncertainty. First, we present a new optimization framework that combines robust optimization, to take into account breathing motion uncertainty, with a conditional value-at-risk (CVaR) representation of clinical dose-volume criteria. This framework is general and applicable to any problem with an underlying loss/return distribution that changes over time based on the state of some system. We then explore a range of constraint generation solution strategies to solve the resulting large-scale RO problems and compare the computational efficiency of the proposed approach with that of traditional solution methods. Our computational experiments show that the proposed constraint generation strategies can reduce the solution time by an order of magnitude. Next, we apply our robust method to real data of several breast cancer patients and dosimetrically compare the results with those of the current clinical treatment planning methods. Our results demonstrate that the robust approach can substantially reduce the radiation to the heart and is less sensitive to breathing motion compared to the conventional clinical method. Finally, we apply the concept of Pareto robust optimization (PRO) to breast cancer RT. Using clinical patient datasets, we show that RO and PRO solutions are very close for all patients. We find PRO solutions that have a potentially lower heart dose than RO solutions under non-worst-case breathing scenarios while maintaining the worst-case performance of RO solutions.

Keywords: Breast Cancer
Conditional Value-at-risk
Optimization under Uncertainty
Radiation Therapy
Robust Optimization
Advisor: Chan, Timothy C. Y.
The Effects of Conscious and Primed Learning Goals on the Performance of a Complex Task

Subconscious processes play an important role in employee motivation. This dissertation focuses on the ability to use subtle environmental manipulations to prime a learning goal and thereby improve performance on a knowledge-acquisition task. Previous research (Chen and Latham, 2014) has suggested that a learning goal prime can effectively increase performance on a knowledge acquisition task. However, organizations typically also employ conscious goal setting interventions, leaving unanswered questions about how a conscious and a primed learning goal might operate together to increase performance. To understand these effects, I conducted an experiment with 236 participants, in which I manipulated a primed learning goal (versus control) and a challenging, specific conscious learning goal (versus a do-your-best goal) and assessed performance on a complex scheduling task.

Keywords: Automaticity Model
Goal Setting
Learning Goals
Primed Goals
Priming
Subconscious Processes
Advisor: Latham, Gary P
"You Can't Stop The Bell From Ringing." Protean, Unpredictable, And Persisting: The Victim Impact Statement In The Context Of Sexually Assaulted Women

The victim impact statement (VIS) is a victim’s voluntarily written account of a range of harms experienced as a consequence of a crime. Rarely is the VIS investigated specific to sexual assault or from a theoretical perspective. This qualitative study was designed to address these gaps. Interviews were conducted with 44 participants who sought or provided VIS-related services in Canada. Findings were analyzed using insights from actor-network theory. Findings of the overall study are presented through three distinct but interrelated papers. “Obliging Detours” (Miller, submitted) describes the development of the VIS in Canada, and its multiple, innovative, and unauthorized pathways of use. These pathways created novel opportunities, demands, and risks for sexual assault victims, particularly those who were mothers, female offenders, or had been excluded at trial. “Relational Caring” (Miller, 2014) identifies an ethic of care that underpinned use of the VIS by sexually assaulted women. Victims prioritized the well-being of others by constructing VIS narratives that privileged the harms experienced by others, protected future victims, and promoted the interests of intimate partner offenders. Victims who were mothers, especially those abused as minors, and those who were intimate partners of their offenders were particularly implicated. “Purposing and Repurposing Harms” (Miller, 2013) demonstrates how harm descriptions were manipulated by victims and others in keeping with, and contrary to, legislators’ design of the VIS. VIS repurposing occurred through victims’ practices of strategic disclosure, which was intended to effect changes in others’ behaviours, and harm peddling, which was the circulation of the VIS in nonsentencing arenas by victims and nonvictims to obtain compensation, child custody, and parole delay. Taken together, the findings revealed that the VIS has a protean nature that is produced by structural and relational factors, and lends itself to multiple uses in multiple contexts. VIS-related outcomes and the effects on victims and others could neither be wholly predicted nor prevented, and involved interactions beyond the criminal court setting. The protean, unpredictable, and persisting positive and negative effects of the VIS hold promise—and danger—for sexual assault victims.

Keywords: actor-network theory
Canada
rape
sexual assault
victim impact statement
Advisor: Du Mont, Janice
Disorders of Sleep and Wakefulness among Persons with Traumatic Brain Injury: Prevalence and Impact

Disturbed sleep is a common complaint of persons with head trauma. While the disruption subsides relatively quickly for some, up to half of persons with traumatic brain injury (TBI) report chronic sleep disturbances, which can lead to serious impairments of daytime functioning, impede the rehabilitation process and the return to productive life. Ongoing sleep problems can also contribute to the development of new or exacerbation of pre-morbid medical and psychiatric disorders, constituting additional burden to the already compromised brain and bodily functions of the impacted individual. The scope and systematic reviews comprising this thesis aimed to summarize the current state of knowledge concerning disorders of sleep and wakefulness in the TBI population. The original research described in this thesis is cross-sectional in design and aimed to investigate the relevance of sleep dysfunction to TBI outcomes in Ontario workers with delayed recovery from mild TBI (mTBI). Based on the findings of the reviews, it is apparent early detection of sleep problems in persons with TBI by screening can potentially improve the health outcomes of those affected, and this approach may turn out to be economically beneficial. In a review of fatigue after TBI, fluctuations in frequency were observed over time and several potential risk factors were described. The consequences of posttraumatic fatigue were not entirely clear, however, a relationship between fluctuations in sleep quality and fluctuations in fatigue frequency was reported. The findings of the original research carried out show outcomes in workers with mTBI may differ based on the presence of absence of insomnia, head and/or neck pain, and marital status. Furthermore, insomnia was found to be highly prevalent in the studied population and factors associated with insomnia are clinical and non-clinical. The thesis emphasizes conceptual frameworks of community integration and sleep dysfunction in TBI, which provides a context for examining a problem, serves in developing future hypotheses, and constitutes a base for observations, research design, and interpretations. Most importantly, it serves as a guide for the systematic study of a precisely defined relationship between variables. The thesis concludes with a summary of the practical implications of the research findings.

Keywords: disability
insomnia
screening
sleep
traumatic brain injury
work
Advisor: Colantonio, Angela
Sub-optimality of Local Algorithms on Sparse Random Graphs

This thesis studies local algorithms for solving combinatorial optimization problems on large, sparse random graphs. Local algorithms are randomized algorithms that run in parallel at each vertex of a graph by using only local information around each vertex. They produce important structures on large graphs such as independent sets, matchings, colourings and eigenfunctions of the graph Laplacian with only constant running time and little memory usage. Hatami, Lovasz and Szegedy conjectured that all reasonable optimization problems on large random d-regular graphs can be approximately solved by local algorithms. This is true for matchings: local algorithms can produce near perfect matchings in random d-regular graphs. However, this conjecture was recently shown to be false for independent sets by Gamarnik and Sudan. They showed that local algorithms cannot generate maximal independent sets on large random d-regular graphs if the degree d is sufficiently large. We prove an optimal rate of failure of this conjecture for the problem of percolation on graphs. The basic question is this. Consider a large integer T, which we consider a threshold parameter. Given some large graph G, find the maximum sized induced subgraph of G whose connected components have size no bigger than T. When T equals 1 this is the problem of finding the maximum independent sets in G. We show that for asymptotically large values of the degree d, local algorithms cannot solve the percolation problem on random d-regular graphs and Erdos-Renyi graphs of expected average degree d. Roughly speaking, we prove that the largest induced subgraph with a given threshold that local algorithms can find is no more than half of the maximum possible size. This is optimal because there exists local algorithms that can find such induced subgraphs of half the maximum size. Part of this thesis represents joint work with Balint Virag.

Keywords: Computer Science
Ergodic Theory
Probability Theory
Stochastic Processes
Advisor: Virag, Balint