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Allometric options for predicting tropical tree height and crown area from stem diameter in Central Africa
Get PDFAllometric equations relating stem diameter to height (H–D) and crown area (CA–D) are widely applied to estimate forest structure and biomass. Few studies, however, have assessed whether differences in H–D and CA–D models among forest types are driven by species variability or plasticity. We examined six forest types in Central Africa to test the contribution of species variability and evaluate whether models incorporating forest-type data improve predictive accuracy. Data included 845 trees (52 species, 49 genera, 17 families). Variance partitioning showed that H–D allometry varied significantly among forest types, with diameter, forest type, and species jointly explaining 80% of variance. Excluding forest type increased the variance explained by species from 9% to 14%. For CA–D allometry, predictors explained 72% of variance, with independent effects of forest type (2%) and species (5%). Removing forest type did not shift variance toward species. Models incorporating forest-type information consistently yielded lower prediction errors than generalized models. These results demonstrate that species variability is the dominant driver of allometric relationships in Central African forests, although the balance between variability and plasticity differs between height and crown dimensions. Our findings highlight the importance of forest-type-specific allometric models for accurate carbon stock estimation and remote sensing calibration.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
Investigating factors underlying myelinating glial cell development and maturation and engineering repair Schwann cells for clinical transplantation
Get PDFThe peripheral nervous system (PNS) is a bridge between the central nervous system (CNS) and various regions of the body. Axons grow between the CNS and PNS, linking the two divisions. Myelinating glial cells are oligodendrocytes in the CNS and Schwann cells in the PNS. These glial cells wrap a myelin sheath along the length of axons, allowing for efficient signal transduction, supporting axons, and enabling proper neurodevelopment, function and overall preservation of the axon. Degenerative disorders such as multiple sclerosis and amyotrophic lateral sclerosis are associated with oligodendrocyte dysfunction, while Charcot-Marie-Tooth disease is associated with Schwann cell dysfunction. These disorders are widely prevalent and currently have no cure, greatly impacting the patient’s quality of life, shortening life expectancy and placing significant strain on the healthcare system. Additionally, Schwann cells are critical for successful peripheral nerve regeneration after injury, clearing debris, recruiting immune cells, secreting neurotrophic factors to aid regeneration of the damaged axon and rewrapping nerves in a protective myelin coating. However, Schwann cells rapidly lose their initial capacity to remyelinate nerves within days of injury, worsening with advanced age and resulting in lifelong neuropathic pain and dysfunction. In this dissertation, I investigated the molecular mechanisms underlying the development and maturation of myelinating oligodendrocytes in the spinal cord and Schwann cells in the periphery, with a focus on development, maturation and repair processes. First, I explored whether transcription factors downstream of the MEK/ERK signaling cascade, particularly Etv5, are crucial in regulating nerve integrity and the repair phenotype in the PNS (Chapter 2). I then examined the role of Etv5 in controlling the fate specification of myelinating glial cells in the spinal cord and found that Etv5 is required for the development and lineage maturation of oligodendrocytes (Chapter 3). Finally, since peripheral nerve repair can be achieved by transplanting Schwann cells, I overexpressed transcription factors in a combinatorial fashion to successfully engineer repair Schwann cells from fibroblasts for clinical transplantation (Chapter 4). Taken together, my work has provided new molecular insights into how myelinating glial cells are generated, with implications for degenerating diseases of the spinal cord and nerve.Ph.D
Motor imagery of joint action is shaped by assumed partner abilities and challenged by cognitive demands
Get PDFMotor imagery (MI) is a motor-cognitive process involving the mental rehearsal of movement without actual physical execution. When imagining joint actions, individuals must not only imagine their own movements but also integrate those with the imagined movements of a partner. Although previous research has shown that MI of joint action is possible, the field remains underexplored. The overarching purpose of this dissertation was to explore the social and cognitive dynamics of MI in joint action contexts. Specifically, this dissertation describes five experiments where participants performed and imagined performing a serial disc transfer task alone and with imagined partners of varying abilities. Imagined movement time (MT) was used to examine whether participants considered the assumed abilities of a partner when imagining performing the task, and to assess the cognitive demands involved in imagining the joint task. Five main conclusions were derived from this research: 1) individuals adjust their imagination of a partner’s movements based on the assumed motor abilities of the partner; 2) adjustments to an imagined partner’s movements influence the imagination of the imagers’ own movements; 3) most individuals are aware that their own imagined movements are affected by a partner’s perceived abilities, although these adjustments occur unintentionally; 4) individuals have difficulty controlling their own imagined movements, particularly when paired with a high-performing partner; and 5) imagining a serial joint action task is more cognitively demanding than imagining the same task performed alone. Overall, this research demonstrates that MI of a serial joint action task is cognitively demanding and can be adjusted to account for the assumed abilities of a partner, which in turn affects one’s ability to control their own imagined movements. These findings offer a novel contribution to the study of MI and joint action.Ph.D
Essays on Labor Economics: Interventions and Behavior
No full textThis dissertation explores behavioral responses to policy interventions through three empirical studies. The chapters draw on a combination of administrative, experimental, and survey data to examine the effects of immigration policy, information frictions, and the provision of public goods. The overarching theme is to understand agents, be they firms, students, or workers, react to sudden changes in policy or information environments, and how these responses shape their outcomes.
The first chapter studies the effects of increased immigration on the performance of local firms and their workers, leveraging a sharp increase in Canada's immigration targets in 2016. The policy led to an influx of predominantly high-skilled workers and generated unexpected variation in the growth of the foreign-born population across regions and nationalities. I quantify firms' exposure to the shock using a shift-share instrument and draw comparisons across firms that operate within the same labor market based on differences in worker origins. I find that employers more exposed to the shock accelerated the hiring of recent arrivals who lacked locally accumulated human capital, increased employment and compensation for both immigrant and native workers, and experienced expansions in both total output and output per worker. These results are consistent with firms benefiting from immigration through workplace ethnic networks, which may help identify workers' productivity characteristics that are otherwise overlooked in the labor market.
The second chapter, joint with Marc-Antoine Châtelain, Paul Han, and En Hua Hu, examines how individuals form and update beliefs in the presence of misspecification in the data generating process. Using high-frequency data from a large undergraduate course, the study documents persistent overconfidence in students’ grade expectations, and a systematic overestimation of grading noise. An experimental intervention that provides information about noise leads to a 32% reduction in prediction errors. Structural estimates indicate that at least 25% of prediction errors are attributable to misspecified priors. These results highlight the role of subjective model in belief updating, and suggest that simple interventions can significantly improve information processing.
The third chapter, co-authored with Kourtney Koebel, analyzes how universal childcare policy in Québec, which led to sharp increase in demand for their service, affected the labor market for childcare workers. Using Canadian Census data and administrative reports from Québec, we find that the policy roll-out coincided with a sharp decline in caregiver qualifications, offering a potential explanation for the negative effects on children documented in earlier studies. Earnings for workers improved under the policy, counter to concerns that government monopsony power would dampen wage growth. Hourly earnings rose significantly for center-based workers, who were generally covered by the subsidy. Wages for home-based workers, who were largely unsubsidized, remained flat, or declined in regions that saw rapid expansion in regulated care. We also find that this latter group increasingly served lower-income families, raising concerns about unequal access to high-quality care.Ph.D
Risk-Aware Control of Cone-Bounded Nonlinear Systems
Get PDFThe optimal control of stochastic nonlinear systems is difficult in general, and introducing risk-awareness only compounds the difficulty. Motivated by this, we propose a risk-aware, suboptimal controller design applicable to a general class of stochastic systems with both additive and multiplicative disturbances. Moreover, the proposed controller is computationally tractable, admitting a Riccati-like form. To develop this controller, we build upon earlier work to develop a theory of cone-bounded functions between Banach and Hilbert spaces that allows for more precise cone-bounds. This enables us to then extend this work to a novel class of quasi-cone-bounded systems. By deriving key properties of such systems, we are able to derive a suboptimal controller with guaranteed regulation upper bounds. Finally, we present a reformulation of variance suppression allowing us to extend that notion of risk-awareness to nonlinear systems, and therefore to (quasi-)cone-bounded suboptimal controllers.M.A.S
Having it All? A Phenomenological Exploration of Women's Sense of Fulfilment
Get PDFUsing reflective lifeworld research (Dahlberg et al., 2001), a qualitative, phenomenological method, this study explored the phenomenon of having it all yet not feeling fulfilled. The experience of successful women feeling unfulfilled at midlife is pervasive while at the same time there is a general lack of research. The purpose of the study was to gain a better understanding of the phenomenon through an in-depth exploration of women’s experiences. Open-ended semi structured interviews were completed with seven women in their forties who lived in Ontario. Study participants self-identified as successful yet experiencing a sense of feeling unfulfilled. The broader essence identified by participants was a feeling of dissonance between how they feel and what they have achieved. This manifested in eight themes: a sense of ennui (feeling = bored), experiencing incongruence (feeling = internal tension/anxiety), the weight of expectations (feeling = pain), a lack of direction (feeling = lost), making compromises (feeling = frustration), a sense of disillusionment with world (making a difference) (feeling = disheartened), experiencing fatigue (feeling = spent), and the perception of being undervalued (feeling = sad). Integrated findings included the identification of the phenomenon as a marker or motivator for change, the shifting perspective of career success from objective to subjective, the intersection between mid-life and self-identity and the importance of values awareness and alignment. These findings help to bring awareness to this phenomenon as it relates to well-being and career development theory, policy and practice. From a policy perspective the nuanced understanding of career constructs, including career, purpose, work-life balance and the relationship between success and fulfilment were discussed. The importance of considering this phenomenon in practice was considered both from the perspective of the individual and in a therapeutic setting.Ed.D
Applying machine learning methods to describe complex medication use in a population of community-dwelling older adults living with dementia: lessons for pharmacoepidemiology studies using health administrative data
Get PDFPersons living with dementia often have complex medication use due to symptoms related to dementia and comorbidities that accumulate as individuals age. Understanding the consequences of using multiple medications in combination, that is, the potential risk of interactions between medications being used concurrently, is important to optimizing medication use, and reducing related adverse events. Unsupervised machine learning methods offer an opportunity to incorporate more data about exposure to multiple medications into pharmacoepidemiology methods to better understand prescribing patterns and medication related adverse events. This thesis examined the application of two unsupervised machine learning methods – network analysis and hierarchical clustering – to describe polypharmacy and fall-related hospitalizations over time in a population-based cohort of community-dwelling older adults with incident dementia in three related studies in linked health administrative data. In Paper One, network analysis described the common medication subclasses concurrently prescribed within persons living with dementia at case ascertainment and five years following. In Paper Two, hierarchical clustering found groups based on medication use were associated with comorbidities. In Paper Three, there was an association between the CNS-active medication prescribing cluster (individuals with similar, higher-than-average CNS-active medication use) and fall-related hospitalizations, a potentially medication-related adverse event, even when controlling for sex, age, potentially inappropriate prescribing, and level of polypharmacy. Collectively, the results from these studies demonstrate the benefits (and limitations) of unsupervised machine learning methods – including hypothesis generation, data reduction, and summarizing complex information visually – in pharmacoepidemiology studies. From a population health perspective, in persons living with dementia, this thesis provided an overview of prescribing patterns, demonstrated the importance of cardiovascular and CNS-active medications (particularly the latter’s association with falls), and highlighted the need for proper management and treatment of comorbidities alongside the management of dementia.Ph.D
Molecular Signatures of Early-Onset Bipolar Disorder and Schizophrenia: Transcriptomic and Machine-Learning Insights into Calcium and cAMP Signaling, Including Sex-Specific Patterns
Get PDFEarly age of onset is a major predictor of poor disease course in Bipolar Disorder (BD) and Schizophrenia (SCZ), often associated with greater symptom severity, cognitive decline, and worse outcomes. However, the biological mechanisms that shape age- and sex-specific vulnerability remain unclear, limiting progress toward early identification and intervention. To address this gap, we conducted an integrative transcriptomic study of 369 postmortem dorsolateral prefrontal cortex samples from the CommonMind Consortium. Differential gene expression, Weighted Gene Co-Expression Network Analysis, and gene set enrichment analysis were applied to identify pathways associated with age of onset, complemented by sex-stratified models and cellular deconvolution. To assess predictive signals, we applied a rigorous two-stage machine-learning framework using nested cross-validation, with Lasso feature selection followed by L2-regularized logistic classification. Performance was evaluated solely on held-out test folds. Genes and modules linked to earlier onset showed consistent enrichment for calcium signaling, with downregulation of <i>CACNA1C</i> and multiple adenylate-cyclase-related transcripts, while female-specific analyses revealed selective dysregulation of cyclase-associated pathways. Network analysis identified a calcium-enriched module associated with onset and sex, and diagnosis-specific modeling highlighted <i>MAP2K7</i> in early-onset BD. The predictive model achieved an AUC of 0.63, and the top 50 machine-learning features were significantly enriched in calcium signaling pathway. These findings converge on calcium&ndash;cAMP signaling networks as key drivers of early psychiatric vulnerability and suggest biomarkers for precision-targeted interventions
On Density and Equidistribution of Stationary Geodesic Nets
Get PDFStationary geodesic nets are embedded graphs in a Riemannian manifold which are stationary with respect to the length functional. In this thesis, we study the distribution of closed geodesics and stationary geodesic nets in Riemannian manifolds. We prove that for a generic set of metrics on a closed manifold , , the union of all the embedded stationary geodesic nets in forms a dense subset of . For , we prove that for generic metrics on we can obtain an equidistributed sequence of closed geodesics. This means that there exists a sequence of closed geodesics such that for every open subset of ,
\begin{equation*} \lim_{k\to\infty}\frac{\sum_{i=1}^{k}\length_{g}(\gamma_{i}\cap U)}{\sum_{i=1}^{k}\length_{g}(\gamma_{i})}=\frac{\Vol_{g}(U)}{\Vol_{g}(M)}.
\end{equation*}
We show that the previous equidistribution result also holds for but replacing closed geodesics by stationary geodesic nets. The main tool that we use is Almgren-Pitts Min-Max Theory, in particular the Weyl law for the volume spectrum. We also prove a Structure Theorem for stationary geodesic nets analogous to that of Brian White for minimal submanifolds, which is used to prove the density and equidistribution results. The density result was obtained in collaboration with Yevgeny Liokumovich, and the equidistribution result in dimensions and is joint work with Xinze Li.Ph.D