VictorJuiz/thesis huggingface dataset:
The Influence of Ontogeny and Physiological Microbial Exposure on Macrophage Maintenance and Function
Keywords: atherosclerosis
inflammation
innate immunity
macrophages
monocytes
ontogeny

Macrophages are highly phagocytic cells found in almost every tissue of the body and are involved in several physiological processes, including pathogen defense and tissue development. The work presented in this thesis sought to determine whether factors such as ontogeny and microbial diversity can affect macrophage maintenance and function in homeostatic conditions and disease. First, we isolated and characterized a unique population of macrophages that exists in the vasculature during steady state. Using lineage-tracing techniques we demonstrated that adult vascular macrophages derive from embryonic and adult origins. We found that survival and maintenance of this population is dependent on the interaction between the fractalkine receptor and its ligand. This study highlights the importance of tracking the ontogenetic source of macrophages in tissues as we see key differences in maintenance and function between resident and recruited subsets in the vasculature. The second chapter in this dissertation focuses on evaluating whether exposure to diverse environmental pathogens can affect macrophage maintenance and function. It was observed that physiological exposure to microbes significantly alters monocyte and macrophage subsets in mice – specifically, we detected an expansion of resident macrophages in the peritoneum; we note that local proliferation, and not monocyte recruitment, accounts for this change. Microbial exposure did not affect phagocytosis, responses to bacterial pathogens and sepsis, and only slightly altered cytokine production in response to toll-like receptors (TLRs) agonists. In a mouse model of atherosclerosis, we found that microbial exposure reduces lesion development exclusively at 8 weeks. In summary, this work examined the influence of ontogeny and microbial exposure on macrophage function in the steady state and in the course of disease.
The Impacts of Climate and Climate Change on Aviation in the Canadian North
Keywords: aviation
climate change
fog
soil temperature
visibility
wind

Aviation is inherently linked to meteorology as severe weather is often responsible for flight delays, cancellations and sometimes accidents. Climate change is expected to change the Arctic environment and the warming rate in this region is greater than most locations on Earth. With a changing climate, the risks of flying will also be changing. In Canada, many Arctic communities in Hudson Bay, Nunavik in northern Quebec and western Labrador rely heavily on aviation to transport passengers, mail and groceries because they lack road networks or railway to access larger settlements and shipping is limited to brief periods in summer. Using historical hourly and daily climate data, this thesis examines four topics related to flying: 1) wind pattern changes (1971 to 2010) at seven locations around Hudson Bay, northern Quebec and western Labrador; 2) fog and visibility trends at 16 Hudson Bay communities (1953-2014); 3) historic long-term soil temperature trends at 5 to 150 cm depths and future projections under three greenhouse gas concentration trajectories at Kuujjuaq, Quebec; 4) appearance and climate conditions for frostquakes. The results of these topics are: 1) an increase in hourly average and daily maximum wind speed around Hudson Bay region and declining trends in western Labrador, plus prevailing wind direction changed at two communities; 2) fog and ice fog frequencies declined but reduced and low visibility trends varied spatially within the Hudson Bay region; 3) soil warming at approximately 1oC per decade from 1967 to 1995 and future soil temperature will be above 0oC under all projected trajectories at Kuujjuaq; 4) identified that water-saturated soil, minimal snow cover and rapid temperature drop to below freezing causes frostquakes and that observations were somewhat dependent on the density of the observational network. Passengers travelling to and from Hudson Bay will benefit from the results of this research to better understand the risks associated with flying to these communities. Pilots, airport operators and airlines will improve their awareness of this issue and increase their understandings of the risks caused by climate change in this area. Improved safety will be achieved by anticipating, adapting to and mitigating these changes.
Development of a Multifluid Magnetohydrodynamic Model for Anisotropic, Partially Ionized Plasmas
Keywords: computational fluid dynamics
geospace magnetic reconnection
magnetohydrodynamics
MHD
plasmadynamics
plasma modelling

A multifluid magnetohydrodynamic (MHD) model based on an extended fluid dynamics description for each plasma species is proposed for the prediction of the flow and behaviour of fully and partially ionized non-equilibrium anisotropic plasmas. Two-(electrons and ions) and three-fluid (ions, electrons and neutrals) plasma models are described that both make use of a 10-moment or Gaussian anisotropic moment closure of the Boltzmann equation. The moment equations for each plasma species are fully coupled to the Maxwell's equations which govern electromagnetic wave propagation within the plasma and a Bhatnagar-Gross-Krook (BGK) relaxation time approximation is used to model non-equilibrium collisional processes between the plasma species. Chemical kinetic models are included to represent the partially ionized plasma processes. Unlike conventional MHD models, the proposed multi-species MHD model is capable of taking into account large temperature anisotropies and temperature differences between the electrons and ions, both of which can occur for low-density, high-temperature plasmas and/or strongly magnetized plasmas. A second-order Godunov-type finite-volume method is developed for the solution of the one- and two-dimensional forms of the multifluid plasma models, which includes temporal limiting in one-dimension and a parallel scheme utilizing a Newton-Krylov-Schwarz (NKS) implicit algorithm for the two-dimensional solution procedure. The numerical fluxes in the Godunov-type scheme are solved using HLLE and Godunov numerical flux functions. The two-dimensional solution procedure includes Generalized Lagrange Multiplier (GLM) and diffusive error correction schemes for the treatment of divergence errors associated with the electromagnetic field. An accuracy assessment is performed for the two-dimensional numerical solution procedure, demonstrating good convergence of solutions for a range of problems. The validated two-dimensional solution procedure for the multifluid MHD model is then applied to the solution of the well-known Geospace Environmental Modelling (GEM) challenge problem involving magnetic field reconnection and numerical results are compared to established solutions in the literature. Results of grid refinement and parametric studies for the GEM case are also described. The proposed multifluid MHD model is shown to recover known published results with relatively small computational effort and the potential of the proposed treatment for describing a range of non-equilibrium anisotropic plasma flows is demonstrated.
Mechanisms Controlling Cell Size in Animal Cells
Keywords: cell cycle
cell size
G1/S transition
mTOR pathway
p38 MAPK pathway

Although questions on cell size have been investigated for more than half a century, molecular mechanisms that ‘program’ the size of animal cells are only starting to be revealed. My Ph.D. research focuses on the molecular mechanisms that promote cell size uniformity in proliferating mammalian cells. By relying on a high-content small chemical screen, I identified candidate proteins and signaling molecules that may function as cell size specifiers. Intriguingly, analysis of the screen hits suggested a role for the p38 MAPK in the long-sought mammalian cell size checkpoint. In follow-up experiments, I showed that p38 MAPK signaling is activated in small, but not large cells, which selectively inhibits the progression of small cells into S phase. Consistent with this model, chemical and genetic perturbations of p38 resulted in the loss of the compensatory G1 length extension in small cells; cells lacking p38 activity proliferated faster, were smaller in size and displayed increased size heterogeneity. Altogether, my work suggests that the p38 MAPK pathway responds to changes in cell size and regulates G1 exit accordingly, to increase cell size uniformity. In this thesis, I first present an in-depth review of the animal cell size research. Reflecting on literature, I summarize in Chapter 1.1 a convergence of historical and recent evidence that support size sensing as a cell-autonomous function of individual animal cells. I also discuss the historical debates on animal cell size sensing and offer my understanding of how these “conflicting” literature may be resolved through new interpretations. In Chapter 1.2, I discuss in detail how cell size affects cellular, tissue and organismal level functions. I hope this inspires more functional and mechanistic research on cell size in the future. In the last Chapter, I further discuss the implications of the p38 signaling and cell size control and introduce in brief the branches of follow-up research that emerged from my thesis work.
Entries to Intimacy: Shared Solitude in Garth Greenwell's What Belongs to You, Anne Carson's Nox, and Roni Horn's Another Water (The River Thames, for Example)
Keywords: Anne Carson
Garth Greenwell
Language and literature
Queer Theory
Roni Horn
Visual Studies

This dissertation studies three books that unfold as inquiries into the possibility of being in relation. I argue that Garth Greenwell’s What Belongs to You, Anne Carson’s Nox, and Roni Horn’s Another Water (The River Thames, for Example) attest to a form of togetherness that rests not on recognition or perception, but rather on the sense of a space that remains without relation. Readings these books in light of Michel Foucault’s description of the archive, and Giorgio Agamben’s theorization of thought, I show that this space marks the very place where relations emerge, a place, therefore, that exceeds both sight and thought. The books not only present modes of seeing, knowing, or thinking that turn towards this place, but also stage a sensuous engagement with the unseen, unsaid, or unthought. In each chapter, accordingly, I read scenes that both trace an experience that eludes the seeing or knowing subject, and bring the reader in touch with a space beyond relation. Drawing, in turn, on William Haver’s notion of an erotics of thought, Roland Barthes’ theory of photography, and Maurice Blanchot’s theorization of the essential solitude, I delineate the ways in which these exemplary scenes affirm the impossibility of resolving the question of how to be with others. To engage this impossibility, the books suggest, is to open up relations to possibilities unforeseen.
Machine Learning Methodologies for Uncovering the Mechanisms of Complex Diseases
Keywords: Compex disease
Computational biology
Genetics
Healthcare
Machine learning

Identifying the mechanisms associated with complex human diseases is one of the main challenges of human genetics and computational medicine. With every technical advance such as the ability to sequence whole genomes and transcriptomes faster and cheaper, there is the promise of finally discovering the root causes of complex genetic diseases and leading the way for efficient personalized medicine. That promise have not been fulfilled yet despite the technological advances and large datasets gathered. All the variations discovered to be statistically associated with a disease can only account for a small proportion of the genetic component of the disease. Given the complexity of the problem, we need to move beyond the state-of-the-art statistical tools and use advanced machine learning techniques that can better fit the complexity of the problem. In this thesis, we propose machine-learning methods that are designed specifically for the biological problem in order to increase the power of identifying mechanisms of complex diseases. We present approaches that can integrate multiple types of data when each dataset contains only a part of the disease mechanism and we incorporate as much biological knowledge and annotations as possible within our framework. We tackle the problem by simultaneously considering all potential sources of aberrations that can lead to a disease and show that we can find more complex mechanisms explaining the disease in a larger proportion of the patients. Our approaches also provide guidelines to investigate the likely root causes for individual patients opening the way to personalized treatment.
When Every Day is a High School Reunion: Social Media Comparisons and Self-esteem
Keywords: self-esteem
social comparison
social media

Although past research has shown that social comparisons made through social media contribute to negative outcomes, little is known about the nature of these comparisons (e.g., domains, direction, and extremity), variables that determine the outcomes of these comparisons (e.g., post valence, perceiver’s self-esteem), and how these comparisons differ from those made in other contexts (e.g. while texting or interacting face to face). In five studies (N=900), I provide the first comprehensive analysis of how individuals make and respond to social comparisons on two different social media platforms (Facebook and Instagram), using comparisons made in real-time while participants browsed their own social media news feeds (Studies 1 and 3), experimenter-generated social media content (Study 2), and reports of comparisons made in various contexts, including social media (Studies 4 and 5). I found that individuals made frequent upward comparisons on social media. Further, social media comparisons were more likely to be upward than downward, and making more frequent and more extreme upward comparisons on social media resulted in greater declines in self-evaluations, mood, and life satisfaction. In addition, individuals with lower self-esteem made more frequent and extreme upward comparisons while browsing social media, resulting in even steeper declines in self-evaluations. Finally, compared to upward comparisons in other contexts, those made on social media were more often to distant (vs. close) targets, more likely to be image-based, and resulted in greater declines in self-evaluations. Together, these studies provide the first insights into the cumulative impact of multiple social comparisons, demonstrate the unique nature of social comparisons made on social media, and clarify the role of self-esteem in online social comparison processes.
Artisanal Mines, Governance and Historical Generations in the Congo Copperbelt
Keywords: Artisanal Mining
Central Africa
Postcolonialism
Social Change

What insights about social change emerge when we analyze the liberalized present as a temporal period comprised of a palimpsest of generational experiences, recursive elements and residual layers of the past? This thesis is a response to this question through a look at the Congolese mining sector from the perspective of individuals who are often marginalized by it or rendered less visible due to a popular emphasis on the intractable problems of the Congolese state, transnational mining corporations, and the on-going violence in Eastern Congo. The subjects of my inquiry are artisanal miners, customary authorities, state agents working in the artisanal mining sector, retrenched pensioners, and mineworkers’ families. Analyzing how the recently instituted liberalized regime of mining is given form through the interaction between a diverse range of social groups is intended to elucidate the distinctiveness of the (neo)liberalized present relative to the regimes of mining it purportedly replaced. To be precise, I am referring to pre-colonial modes of resource extraction and, their successor, the Belgian colonial regime of mining that was inherited and maintained after Congolese independence. Interrogating how the dynamics of mining in existence today are qualitatively different to the past is an attempt to analyze social change by comparing the dynamics of the present with the succession of political topographies governing mining in the past. Understanding how the various regimes of mining succeed, overlap and compare with one another allows this study to ask: how post-colonial is the present in the Congo Copperbelt? In doing so, this research contributes to other scholarly attempts aimed at understanding the structural continuities and discontinuities that define how the global economic order differentially impacts resource-rich countries like the Congo. In the thesis, I demonstrate that the contemporary unfolding of late capitalism in the Congo Copperbelt is a complex mix of different durées whose overlapping in the everyday lives of miners, local authorities and residents reveals the unfinished nature of the colonial encounter. What this signifies in the now-liberalized Congo Copperbelt is that for a wide range of actors in the resource extraction sector, there has been negligible substantive social change in society.
Using Photo-Elicitation Methods to Explore Spirituality among Persons with Alzheimer’s Disease and Related Dementias
Keywords: Alzheimer's Disease
Dementia
Participant-Inclusive
Photo-Elicitation Methods
Social Work
Spirituality

Alzheimer’s disease (AD) and related dementias involve irreversible memory decline, personality changes and other neuropsychiatric and cognitive impairments for which there is currently no cure. Research has shown that spirituality can be a beneficial coping mechanism to deal with the deleterious psychosocial aspects of disease progression. The central objective of the present study was to examine the experiences of spirituality from the perspective of persons’ who suffer from dementia since no empirical research from a social work perspective currently exists as a basis for enhancing knowledge and practice. Using a participant-inclusive qualitative research methodology of photo-elicitation and qualitative interviews, this inquiry explored the relationship between spirituality and persons with dementia by directly soliciting their views and experiences. Personhood, social constructivism, and symbolic interactionism informed the theoretical basis for this study and purposive sampling was used. The group of participants included 12 persons with a mild-moderate dementia diagnosis, and the methodology was modified in the field to accommodate participant preferences in selecting existing photos as well as taking new ones, which was then followed by in-depth, semi-structured interviews (N = 12). Thematic analysis techniques resulted in the emergence of four core themes. Participants’ rich accounts illustrated their ongoing engagement with spirituality in their daily lives, suggesting that, those with dementia can communicate integrated, nondualist definitions of spirituality. Participants described different ways of accessing spirituality, for example, through adherence to spiritual or religious practices, participation in the arts, reminiscence, humanitarian service, and reflecting on the lives of family members. While dementia impacted aspects of how participants experienced spirituality, they did not abandon it but instead adapted spirituality in order to continue to engage. The core findings in this research underscored the importance of self-defined meaning and purpose for those with dementia, while highlighting the significance of relationships to enhancing quality of life. The results of this study include suggestions for broadening future social work gerontological practice and education so that as the number of older adults diagnosed with dementia increases significantly we may more competently address their needs within an ongoing ethic of care.
Optimizing Big Data Analytics Frameworks in Geographically Distributed Datacenters
Keywords: Apache Spark
Data analytics
Graph analytics
MapReduce
Software-defined networking

A variety of Internet applications rely on big data analytics frameworks to efficiently process large volumes of raw data. As such applications expand to a continental or even global scale, their raw data input can be generated and stored in different datacenters. The performance of data analytics jobs is likely to suffer, as transferring data among workers located in different datacenters is expensive. In this dissertation, we propose a series of system optimizations for big data analytics frameworks that are deployed across geographically distributed datacenters. Our works optimize the following three components in their architectural design: Inter-datacenter network transfers. Few measures have been taken to handle the unpredictability and scarcity of inter-datacenter available bandwidth. With the awareness of job-level performance, we focus on expediting inter-datacenter coflows, which are collections of parallel flows associated with job-level communication requirements. We propose novel scheduling and routing strategies to minimize the coflow completion times. These strategies are implemented in Siphon, a software-defined overlay network deployed atop inter-datacenter networks. Shuffles. Data analytics frameworks all provide a set of parallel operators as application building blocks to simplify development. Some operators trigger all-to-all transfers among worker nodes, known as shuffles. Shuffles are the source of inter-datacenter traffic, and its performance is critical. Our work focuses on improving the network utilization during shuffles, by adopting a new push-based mechanism that allows early start of individual flow transfers. Graph analytics APIs. Graph analytics is among the most important algorithms that are natively supported by typical big data analytics frameworks. Bulk Synchronous Parallel (BSP) is the state-of-the-art synchronization model to parallelize graph algorithms, which generates a significant amount of traffic among worker nodes iteratively. We propose a Hierarchical Synchronous Parallel (HSP) model, which is designed to reduce the demand for inter-datacenter transfers. HSP achieves this goal without sacrificing algorithm correctness, resulting in a better performance and lower monetary cost. We have implemented and tested the prototypes based on Apache Spark, one of the most popular data analytics frameworks. Extensive experimental results on real public clouds across multiple geographical regions have shown their effectiveness.