VictorJuiz/thesis huggingface dataset:
Peer Similarity and Use of Online and In-person Supports Amongst Adult Children Caregivers: A Mixed Method Study

Background: Due to current demographics, adult children are increasingly caring for an elderly parent, which can threaten their health. Social support from similar peers can mitigate caregiving-related health declines. Studies have only explored ‘peer similarity’ within the intervention context, limiting our understanding of its role in naturally occurring support. Many carers are turning to the Internet for convenient and efficient access to peer support. Literature to date has largely focused on Internet-based interventions, overlooking carers’ everyday engagement in peer support across communication modalities. Objective: To explore: 1) the relationship between peer similarity and perceived support; and 2) carers’ experiences with online and in-person peer support. Methods: A mixed method study guided by the Interactional Cognitive Model of Social Support. Twitter was used as an innovative recruitment avenue similar to snowball sampling. A web-based survey measured peer similarity and perceived support. Interviews explored carers’ perspectives on peer similarity and experiences with online and in-person peer support. A hierarchical regression analyzed quantitative data and interviews were thematically analyzed. Results: Seventy-one adult children carers (ACCs) participated, with 15 completing qualitative interviews. The mean age of ACCs was 51 and 90% were daughters. Thirty-eight percent of carers were recruited through Twitter and found to be demographically comparable to those recruited through other strategies. ACCs mobilized their existing networks for support and used a blend of communication modalities to meet practical and relational support needs. Type of support received was consistent across online and in-person modalities. Peer similarity positively and significantly influenced perceived support. ‘Shared caregiving experience’ was described as the most important aspect of similarity since it was multi-faceted and optimized support and relationship quality. Conclusion: Interventions for ACCs should emulate their naturally pragmatic support-seeking style. ‘Shared caregiving experience’ and its various dimensions should be comprehensively investigated to inform measurement instruments and peer-matching interventions.

Keywords: Caregiving
Internet
Online
Peer Support
Social Support
Twitter
Advisor: Cameron, Jill I
Living Arrangements and Intergenerational Support Among Immigrant and Canadian-born Seniors

In the context of population aging, growing scholarly attention has been paid to intergenerational relations between seniors and their adult children. However, with increasing proportions of the senior population being foreign born, scholars of family gerontology and immigrant scholars have not joined forces to study intergenerational relations in later-life immigrant families. This dissertation addresses this gap in the literature by examining nativity differences in three aspects of intergenerational relations: living arrangements, intergenerational economic support, and grandchild care. Using pooled data from Canadian censuses and the National Household Survey (NHS), the first analytical chapter finds that, from 1981 to 2011, the higher propensity for immigrant seniors to coreside with their adult children compared to Canadian-born seniors continued to increase. A regression decomposition approach further reveals that the most important factor underlying these temporal trends is shifting immigrant source regions towards countries where intergenerational coresidence is more of a norm. Focusing on coresidential households, the second analytical chapter finds diverse patterns of intergenerational economic support based on nativity status of both elderly parents and adult children and on race. These patterns are explained by compositional differences in demographic and socioeconomic characteristics of adult children more than by those characteristics of elderly parents. Finally, the third analytical chapter examines nativity differences in occasional and regular grandchild care using the General Social Survey (GSS) Cycle 21 and Cycle 25. Immigrant grandfathers with immigrant adult children are less likely to assist with any grandchild care compared to Canadian-born grandfathers, but no nativity difference is found among grandmothers. In addition, compared to those in Canadian-born families, immigrant adult children have lower odds of regularly using child care by grandparents versus using parental care only. Implications of these findings are discussed in relation to the importance of adding a family perspective to studies on immigrant seniors and the importance of ascertaining the underlying factors of nativity differences in intergenerational relations.

Keywords: grandchild care
immigrant seniors
Immigration
Intergenerational relations
intergenerational support
living arrangements
Advisor: Boyd, Monica
Design and Development of a Precision Miniature Multi-DOF Motor Based on Galfenol

Along with the development of robotics, medical and precision machining industry, novel miniature actuators that can achieve large stroke and high precision positioning has attracted tremendous attentions. There are various mechanisms that can be used to transform energy in magnetic, electrical, and thermal forms into mechanical deformation. The impact drive mechanism is distinguished from the other mechanisms because of the geometry simplicity that renders the mechanism a great advantage in miniature actuators/motors. Conventionally, the impact drive actuators/motors employ the piezoelectric material as the driving element which material suffers significantly from the brittle nature. The objective of this thesis is to develop a novel multi-degree-of-freedom in-plane motor employing the impact drive mechanism to achieve high precision and large stroke motion. Because of the excellent robustness, an iron and gallium alloy, Galfenol, has been used as the driving element. This thesis can be divided into three parts. The first part presents a generalized dynamic model of Galfenol for longitudinal magnetostrictive actuators using the energy approach. Methods, limiting the detrimental effect of eddy-current, have been validated. It is found that the Galfenol has an excellent ability of being employed in miniature resonant actuators/motors. The second part exploits a miniature U-shape Galfenol element as the driving element to develop the miniature motor. Because of the special design of Galfenol, the swing motion of the motor arm is achieved which leads to a strengthened performance. The design can not only achieve a maximum linear motion velocity of 4.03mm/s and a maximum carrying weight of 300g, but also a maximum angular velocity for rotation of 2.65rpm. The third part introduces the feedback control of the proposed motor for achieving the large stroke and high precision positioning with the amplitude modulation and the frequency modulation been explored. Employing the nonlinear amplitude modulation, a positioning accuracy of 500nm is achieved with a finest step resolution of 300nm. Also, this design is capable of achieving a positioning accuracy of 100um in the large stroke motion mode. It is anticipated that this work will provide a preferable choice for broader applications in aforementioned fields.

Keywords: Galfenol
Impact Drive Mechanism
Miniature Multi-DOF Motor
Nonlinear Magnetization
Precision Positioning
Advisor: Zu, Jean
Measurement-device-independent Quantum Cryptography

Quantum key distribution (QKD) enables two legitimate parties to share a secret key even in the presence of an eavesdropper. The unconditional security of QKD is based on the fundamental laws of quantum physics. Original security proofs of QKD are based on a few assumptions, e.g., perfect single photon sources and perfect single-photon detectors. However, practical implementations of QKD systems do not fully comply with such assumptions due to technical limitations. The gap between theory and implementations leads to security loopholes in most QKD systems, and several attacks have been launched on sophisticated QKD systems. Particularly, the detectors have been found to be the most vulnerable part of QKD. Much effort has been put to build side-channel-free QKD systems. Solutions such as security patches and device-independent QKD have been proposed. However, the former are normally ad-hoc, and cannot close unidentified loopholes. The latter, while having the advantages of removing all assumptions on devices, is impractical to implement today. Measurement-device-independent QKD (MDI-QKD) turns out to be a promising solution to the security problem of QKD. In MDI-QKD, all security loopholes, including those yet-to-be discovered, have been removed from the detectors, the most critical part in QKD. In this thesis, we investigate issues related to the practical implementation and security of MDI-QKD. We first present a demonstration of polarization-encoding MDI-QKD. Taking finite key effect into account, we achieve a secret key rate of 0.005 bit per second (bps) over 10 km spooled telecom fiber, and a 1600-bit key is distributed. This work, together with other demonstrations, shows the practicality of MDI-QKD. Next we investigate a critical assumption of MDI-QKD: perfect state preparation. We apply the loss-tolerant QKD protocol and adapt it to MDI-QKD to quantify information leakage due to imperfect state preparation. We then present an experimental demonstration of MDI-QKD over 10 km and 40 km of spooled fiber, which for the first time considers the impact of inaccurate polarization state preparation on the secret key rate. This would not have been possible under previous security proofs, given the same amount of state preparation flaws.

Advisor: Lo, Hoi-Kwong
Qian, Li
The Recognition and Mobility of DNA-Double Strand Breaks

DNA double-strand breaks (DSBs) pose a threat to cell survival and genomic integrity, and remarkable mechanisms exist to deal with these breaks. A single DSB activates a signalling response that profoundly impacts cell physiology, not least through the engagement of DSB repair pathways and the arrest of cell division. Here I study these processes in the budding yeast Saccharomyces cerevisiae and investigate two central themes to this response. First, I examine how the natural ends of chromosomes, telomeres, are differentiated from DSBs by generating DNA ends with increasing telomeric character. I discover a striking transition in the activity of the telomerase inhibitor Pif1 at these ends and propose that this is the dividing line between DSBs and telomeres. Second, I investigate a phenomenon whereby a DSB increases the mobility of chromosomes within the nucleus. This increase in mobility is dependent on the Mec1 kinase and is proposed to promote repair by homologous recombination. I identify that the Mec1-dependent phosphorylation of Cep3, a kinetochore component, is required to stimulate chromatin mobility following DNA breakage and provide a new model for how a DSB affects the constraints on chromosomes. Unexpectedly, I find that increased mobility is not required for DSB repair and instead propose that Cep3 helps arrest the cell cycle in response to a DSB. Finally, my investigation into Cep3 phosphorylation provides new insight into the role of chromatin remodelers and the histone variant H2A.Z in DSB-induced chromatin mobility.

Keywords: budding yeast
chromatin mobility
DNA double-strand break
genome stability
telomere
Advisor: Durocher, Daniel
Molecular Mechanisms of Tumor Dendritic Cell Dysfunction in Cancer

Dendritic cells (DCs) dysfunction in cancer is a well-established phenomenon that is considered one of the key mechanisms of immune evasion. Defects in tumor DCs are caused primarily by tumor-derived factors present in the tumor milieu. However, the mechanisms and the proximal signals that drive this process remain elusive. This thesis explores the molecular mechanisms that drive tumor DC dysfunction. In the first sections of this thesis, I showed the critical importance of tumor-derived toll-like receptor (TLR)-2 ligands in the generation of immunosuppressive Gr-1+ IL-10-producing human and mouse DCs. TLR2 activation induced two parallel synergistic process that converged to activate STAT3: stimulation of autocrine IL-6 and IL-10, and upregulation of their respective cell surface receptors. These processes imprint the capacity of tumor DC in the milieu to respond to lower concentrations of tumor associated cytokines, therefore lowering the STAT3 activation threshold. I identified versican as a soluble tumor-derived factor that ligates with TLR2 to induce DC dysfunction. In the last section of the thesis, I explored the possibility of TLR2 blockade to enhance the efficacy of tumor immunotherapy. TLR2 blockade improved intra-tumor DC immunogenicity. These functional properties was associated with better anti-tumor immune responses elicited by a GM-CSF producing whole cell tumor vaccine (GVAX), and higher rates of proliferation and expansion of adoptively transferred cytotoxic T cells (CTLs). Overall, the findings presented in this thesis provide a basis of understanding the molecular mechanisms of DC dysfunction in cancer and highlight TLR2 as a relevant therapeutic target to improve cancer immunotherapy.

Keywords: Cancer
Dendritic Cells
Signalling
TLR2
Tumor Microenvironment
Advisor: Cattral, Mark S
Phase Partitioning during the Formation of Secondary Organic Aerosol

A sound parameterization of the gas-particle partitioning process is essential for understanding and quantifying secondary organic aerosol (SOA) formation. This thesis aimed to improve the understanding and description of phase partitioning during SOA formation through a combination of both laboratory and modeling studies. Partitioning of organic compounds between gas and particle phase is influenced by the presence of a large quantity of inorganic salts in aerosol, which is known as the salt effect. The salt effects of atmospherically relevant inorganic salts for a large number of organic compounds with various functional groups were measured in this study. The results revealed the importance of both salt species and organic compound identities on the salt effect, with the former as the dominant determinant. Models in predicting salt effect were calibrated and evaluated using the experimental data. Salt effect in mixtures was also investigated, which assists the understanding of salt effect in mixture salt solutions, including aerosols. A new approach for predicting gas-particle partitioning during SOA formation based on quantum chemical calculations was presented, which considers the partitioning species explicitly and captures the dynamic aspects of the aerosol formation processes. The role of different atmospheric parameters and chemical properties (organic loading, liquid water content, salinity, chemical ageing, etc.) was investigated and compared. Performance of the model was found to be comparable to the best currently used group contribution methods. SOA formation from constant emission and oxidation of precursor compounds was simulated to resemble the realistic scenario in the ambient atmosphere. The differential yield that describes the amount of SOA formed from a certain amount of added oxidation products was introduced, which is more relevant for SOA formation in the ambient atmosphere. The necessity of considering kinetic processes in addition to the thermodynamic equilibrium process was also discussed.

Keywords: aqueous phase
atmospheric aerosol particles
phase partitioning
salt effect
Setschenow coefficients
SOA
Advisor: Wania, Frank
Bayesian Applications in Financial Econometrics

This thesis consists of three chapters in Bayesian financial econometrics. The three chapters apply both Bayesian nonparametric and parametric methods to financial market and macroeconomic time series. Chapter 1 extends popular discrete time short-rate models to include Markov switching of infinite dimension. This is a Bayesian nonparametric model that allows for changes in the unknown conditional distribution over time. Applied to weekly U.S. data we find significant parameter change over time and strong evidence of non-Gaussian conditional distributions. Our new model with an hierarchical prior provides significant improvements in density forecasts as well as point forecasts. We find evidence of recurring regimes as well as structural breaks in the empirical application. Chapter 2 studies the joint dynamic behaviour between stock market returns and real economic growth rates. Their relationship is an important empirical question in finance and macroeconomics. This chapter investigates their linkage by proposing a vector autoregressive infinite hidden Markov model. Our model has two advantages over the existing approaches in the literatures. In contrast to Markov switching models with fixed states, our model will learn the number of states from the data rather than fixing it a priori. The vector autoregressive setting in our model allows the joint time series of stock market returns and real growth rates to share the same unobserved state variable. Compared to existing models, our model shows significant improvements in out-of-sample density forecast accuracy. This paper demonstrates the predictive power of stock market returns for future growth rates are better captured by the unobserved states variables, rather than the lagged stock market returns. Chapter 3 studies the predictive power of oil price information for forecasting the U.S. industrial production. Oil price information is divided into two distinct categories: nominal oil price changes and oil price shocks using four definitions proposed in the literature. Previous work has documented lack of predictive relationship of oil price changes but significant predictive power of oil price shocks for U.S. economic growth. However, existing studies focused only on predicting the mean of the economic growth using classical point forecast techniques. As a contribution to the existing literature, we propose a new forecasting model for the analyzed relationship where oil price shocks have the additional flexibility to influence both the mean and the variance of U.S. industrial production. Our forecast is well performed using the Bayesian predictive likelihood as opposed to classical point estimate. We show that the new model for oil price shocks outperforms existing models in terms of forecasting ability. We further confirm previous findings regarding the lack of predictive power of nominal oil price changes.

Keywords: Bayesian Econometrics
Bayesian Nonparametrics
Financial Econometrics
Time Series
Advisor: Maheu, John Mac
Burda, Martin
Strategies for Protein Engineering

Proteins propagate information within a cell by interacting with other proteins, DNA, RNA, and small molecules, enabling a cell to adapt to its environment and to maintain normal cellular functionality. Direct manipulation of a cell's protein interaction network can be achieved by using synthetically designed proteins to replace existing interactions or to create new interactions with other cellular components. A major challenge to engineering new synthetic proteins is the inability to search over the massive space of possible protein variants to identify candidates that bind the biological target of interest. In this thesis, I evaluate existing search strategies and propose a new search strategy for the computational design of proteins, which restricts the search space to one that is enriched for protein variants that tightly bind a protein target. I first evaluated current computational protein design strategies on two biological systems. Using the Fyn SH3 domain bound to different peptide targets, I assessed the design strategies' ability to recover the amino acid variability of the domain core as experimentally determined by phage display. Next, I evaluated the design methods by their ability to engineer the ubiquitin interface for tightly bind towards the USP21 protein. For this assessment, a new parallel validation strategy is introduced. In both biological systems, I found that ensemble protein design strategies outperformed other protein design methods. A limiting factor in current protein design strategies was found to be the accurate creation of alternative protein backbones when a single protein structure was used as a template. I present a flexible backbone design strategy, GP backbone design, that incorporates information from multiple protein structures. I show that using multiple structures to learn a space of possible protein movements increases the number of protein variants that tightly bind a protein target.

Keywords: Computational Protein Design
Protein Engineering
Structural Biology
Advisor: Kim, Philip M
Two Essays on Financial Markets and Institutional Investors

My thesis consists two studies on financial markets and institutional investors. In Chapter 2, I study the trades immediately after the market open and immediately before the market close. The trades in the morning positively predict future returns and cause price continuation. The trades in the afternoon negatively predict future returns and cause price reversals. The momentum trading strategies based on morning returns and the reversal trading strategies based on afternoon returns generate significant abnormal returns, which cannot be explained by standard risk factors including momentum and reversal factors. The results provide strong evidence that trades in the morning are mostly information driven and trades in the afternoon are mostly liquidity driven. In Chapter 3, we explore the properties of equity mutual funds that experience a loss of assets after poor performance. We document that both inflows and outflows are less sensitive to performance because performance-sensitive investors leave or decide not to invest after bad performance. Consistent with the idea that attrition measures the sorting of performance-sensitive investors, we find that attrition has less of an impact on the fundâ s flow-performance sensitivity for institutional funds where there is less dispersion in investor performance-sensitivity. Also, attrition has no effect on the flow- performance sensitivity when attrition arises after good performance or investors invest for non-performance reasons.

Advisor: Christoffersen, Susan