VictorJuiz/thesis huggingface dataset:
Intimate Frontiers: Chinese Marriage Migrants and Contested Belonging in Hong Kong and Taiwan

Based on 17 months of ethnographic fieldwork conducted in Taiwan and Hong Kong between June 2014 and July 2016, this dissertation examines the everyday regulation and negotiation of belonging at various sites of Chinese marriage migrants' personal lives, including social service encounters, domestic space of the home, and Chinese marriage migrant communities. As Chinese women married across the two politically contested borders, their post-migration lives are situated within the frontiers of intimate family lives but also historically grounded political struggles and renewed local discontent against China’s political encroachment. The struggles of belonging faced by Chinese marriage migrants illuminate the norms, values, and ideologies upheld by citizens and the states of Hong Kong and Taiwan. As Chinese marriage migrants yearn to integrate into the Hong Kong and Taiwanese societies, some Chinese marriage migrants mobilized hegemonic discourses of belonging to make meanings of their everyday lives, others contested their exclusion by redefining their identities and in the process, producing new layers of inequalities against less-privileged Chinese marriage migrants. Delving into the narratives of belonging developed in everyday interaction, this dissertation shows how national belonging is a regulated and negotiated process beyond legal categories and immigration policies. This dissertation also shows how class intersects with gender and nationality in producing differentiated regulatory practices and narratives of belonging, illuminating the contradiction and complexity of immigrant belonging in an era of global interconnection and geopolitical tension. Situating the production and negotiation of these narratives within enhanced economic integration and shifting geopolitical entanglement across the China-Hong Kong and China-Taiwan borders, this dissertation also highlights the unfortunate alignment of market logic and nationalist ideology in the formation of discursive national boundaries against immigrants at geopolitically contentious times.

Keywords: Belonging
China
Gender
Hong Kong
Immigration
Taiwan
Advisor: Hsiung, Ping-chun
Choo, Hae Yeon
Development of Solid Oxide Fuel Cell Metal Supports and Intermediate-Temperature Direct Hydrocarbon Anodes

Direct hydrocarbon (DH) solid oxide fuel cells (SOFCs) have the potential to play a role in the transition from high-polluting to cleaner and sustainable electricity generation systems. Moreover, metal-supported DH SOFCs have several advantages that could potentially increase the overall competitiveness of the technology. In this study, bi-layer metal-supported cells were developed using suspension plasma spraying (SPS). The cells were fabricated on bi-layer supports fabricated by powder metallurgy, with microstructures designed to provide a suitable surface morphology for uniform anode deposition. An open circuit voltage (OCV) of 1.105 V at 750 °C in 3% humidified hydrogen was obtained, which deviates from the Nernst potential by only 5 mV. Therefore, the bi-layer support has the potential to minimize cell defects that are known to be detrimental to cell performance. Metal-supported SOFCs containing Cu-Ni-samaria doped ceria (SDC) composites with or without additions of Co or CeO₂, were evaluated for stability against interdiffusion in H₂ at 850 °C. The interdiffusion of Fe, Cr, and Ni was studied, and three protective strategies to prevent the diffusion of Fe and Cr into the Cu-based anodes were evaluated: pre-oxidation of the metal support, application of a protective LaCrO₃ coating to the metal supports, and addition of an SDC interlayer between the metal support and anode. It was found that the most effective stand-alone method to diminish the diffusion of Fe into the anodes containing Co and Ni was the addition of an SDC interlayer between the anode and the metal support. An assessment of the feasibility of using BaTiO₃ as a catalyst for DH SOFC anodes was also performed. The microstructure and electrochemical performance of metal-supported Cu-SDC-Ni-based anodes with or without the addition of CeO₂ and/or BaTiO₃ were evaluated. Metal-supported SOFC anodes were fabricated by a hybrid suspension and solution precursor plasma spraying (SPS/SPPS) process and by SPPS. SPPS Cu-based anodes were found to have better resistance to coarsening than SPS/SPPS Cu-based anodes. The highest power density in this study was obtained for an SPPS Cu-SDC-Ni-BaTiO₃ anode, with peak power densities at 750 °C of 624 mW/cm² and 266 mW/cm² in H₂ and in CH₄, respectively.

Keywords: Barium titanate
Copper-SDC based anodes
Metal supports
Solid oxide fuel cells
Solution plasma spraying
Suspension plasma spraying
Advisor: Kesler, Olivera
Emergency Medical Services Response Optimization

Time-sensitive medical emergencies are responsible for one-third of all deaths worldwide and similarly affect both developed and developing countries. Emergency medical services (EMS) provide rapid out-of-hospital treatment for time-sensitive medical emergencies. In this thesis, we combine optimization and machine learning to solve challenging EMS response problems in two diverse settings: Dhaka, Bangladesh - an urban center in a developing country, and Toronto, Canada - an urban center in a developed country. These settings are unified by uncertainty and stochasticity leading to new robust and chance-constrained optimization problems. In both cities, we employ machine learning to integrate real data with our optimization models. The second chapter develops a unified framework for emergency response optimization under travel time (edge-length) and demand (node-weight) uncertainty that is suitable for developing urban centers. We traveled to Dhaka to conduct field research resulting in the collection of two unique datasets that we leverage to estimate demand for EMS and to predict travel times in the road network. We carefully integrate our predictions and robust optimization model to develop an efficient solution algorithm for large-scale problems. We use our framework to provide an in-depth investigation into four key policy-related questions. The third and fourth chapters focus on improving EMS response for out-of-hospital cardiac arrest (OHCA). Chapter 3 employs a simplified location-queuing framework to quantify the potential benefit from using drones to deliver automated external defibrillators (AEDs) to OHCAs. We demonstrate, using data from 50,000 historical OHCAs covering 26,000 square kilometers around Toronto, that a drone network has the potential to significantly reduce AED delivery time. Chapter 4 develops a two-stage machine learning approach to simulate cardiac arrest incidents and an integrated location-queuing model tailored to the problem of drone-delivered AEDs. Our model combines the p-median framework with an explicit M/M/d queue to determine the minimum number of drones required to meet a pre-specified response time goal (average or 90th percentile), while guaranteeing that a sufficient number of drones are located at each base. We develop a novel reformulation technique that exploits the baseline (EMS) response times, allowing us to optimally solve large-scale instances and provide policy insights.

Keywords: Drones
Emergency medical services
Facility location
Global health
Machine learning
Optimization
Advisor: Chan, Timothy CY
Methods for statistical analysis and prediction of discrete choices

The increasing availability of individual-level consumer data has facilitated the development of new methods for analyzing and predicting people's product choices. This thesis contributes to the existing body of literature with three chapters advancing the statistical analysis of discrete choice. In Chapter 1, I propose a new model seeking to elaborate on the role that choice set composition, known as context, plays in a discrete choice problem. Specifically, I generalize a state-of-the-art class of models stemming from recent research on neural normalization to the multi-attribute setting. I impose a structural model composition based on the brain synaptic plasticity literature, allowing for a particular form of correlation between product utilities. I highlight the properties of the model with a series of experiments and real-world empirical applications. In Chapter 2, I propose a new Monte Carlo method, called Hamiltonian Sequential Monte Carlo (HSMC), for the purpose of nonparametric estimation of unobserved consumer heterogeneity in discrete choice problems. HSMC combines the advantages of Sequential Monte Carlo (SMC) and Hamiltonian transition dynamics. SMC exploits gains from parallelization very efficiently as the core computational load involving the model likelihood is performed by many individual particles independently of one another. At the same time, by using first-derivative information, Hamiltonian transition dynamics has been shown to yield substantial gains in Markov chain mixing properties relative to the standard random walk proposal steps outside of the SMC context. I compare the performance of HSMC with SMC on a discrete choice model of consumer purchases with nonparametric consumer heterogeneity and show the favorable properties of HSMC. In Chapter 3, I propose a Bayesian method called Sequential Optimal Inference (SOI) providing an optimal sequence of questions in experiments. Experiments are frequently used to elicit preferences of potential consumers. Using SOI, the questions are adaptively designed to maximize the expected information and take into account the subjects' previous answers. The method also allows for real-time inference and provides updated posterior distributions while the experiment is performed. Existing methods were created for specific sub-cases. SOI is more general, nesting a large class of models and allowing for a number of inference objectives.

Advisor: Burda, Martin
Gourieroux, Christian
Essays in Interpersonal Economics

Do people vary in their ability to work with others? In Chapter 1 I compare a worker's productivity in solitary production to their value-added to team production to identify team skills: the contribution to team production beyond that given by general skills. The identifying assumption is that workers use general skills in both production functions, but team skills only in team production. Professional tennis provides a useful setting to compare solo work (singles) to teamwork (doubles). I find that 50% of variation in team output is explained by team skills. This is robust to nonlinear production specifications. Players sort positively-assortatively along both skill dimensions, yielding indirect returns to skills of about half the magnitude of the direct returns. Team skills matter beyond tennis. An accumulating body of evidence identifies interpersonal skills as a driver of labour market trends in developed economies, including wage polarization and the emergence of the female labour force. Chapter 2 summarizes an interdisciplinary body of evidence on how interpersonal skills predict tangible life outcomes, with a focus on the labour market. There is convincing evidence that interpersonal skills play a primary role among noncognitive skills, and contribute to the execution of nonroutine tasks. Partnerships can thrive or falter also in the personal realm. Nearly 40% of new marriages will end in divorce, and recent divorcees remarry quickly. This prompts re-examination of the gains to marriage in terms of risk sharing. In Chapter 3 myself and my supervisor Laura Turner explore marriage and divorce when individuals can engage in on-the-marriage search (OTMS). Introducing OTMS allows us to match the rapid remarriage rates seen in US microdata and to explore the connections between infidelity, divorce, and remarriage reported in the sociology literature. In a second-best contracting world, OTMS has ambiguous implications for marriage as a consumption smoothing device and platform for raising children. We find that OTMS has variable effects on the first and second moments of consumption, making women worse off and men better off. Counterintuitively, OTMS has a positive effect on fertility because it increases the attractiveness of having children for men in mediocre marriages.

Advisor: Siow, Aloysius
Scripting and Orchestration of a Knowledge Community and Inquiry Curriculum for Secondary Biology

This dissertation describes a Computer-Supported Collaborative Learning (CSCL) curriculum and corresponding technology environment called CKBiology. Using a design-based research methodology, CKBiology was designed in close collaboration with a high school biology teacher and two software developers, and was implemented in two sections of a Grade 12 Biology course over five design cycles during the 2016-2017 academic year. A pedagogical model called Knowledge Community and Inquiry (KCI) guided the design of CKBiology. Here, students worked as a community to co-construct a shared knowledge base which served as a resource for subsequent inquiry activities. An important aspect of KCI is the design of curricular scripts, which specify the activity sequences, interactions, and roles and responsibilities of individuals within the community. Whereas scripting refers to the structuring of activities before they are run, orchestration refers to the process of executing a script in real-time. This work responds to three challenge areas related to scripting and orchestrating KCI. First, recognizing the high degree of complexity associated with implementing CSCL scripts, one outcome of this work is the development of various student- and teacher-facing learning analytics and software operators that serve to reduce the “orchestrational load” of a KCI community. Second, in orchestrating small group collaborations, another outcome of this work is an evaluation of different group-formation protocols with respect to the collaborative processes, products, and outcomes of the resulting groups. Based on these findings, a series of recommendations is made regarding the ways that different kinds of small groups can be supported in their collaborations. Finally, acknowledging the lack of formalism in the learning sciences for representing CSCL scripts, a third outcome of this work is a series of representations that serve to capture and communicate CKBiology (and KCI scripts more generally) to other practitioners and researchers.

Keywords: active learning classroom
blended learning
computer-supported collaborative learning
design-based research
learning analytics
science education
Advisor: Slotta, James D
Assessing the Metastatic Potential of Cancer Cells with Microdevices

Cancer is a leading cause of death worldwide, and tumor heterogeneity presents a challenge for the clinical management of the disease. The central aim of this thesis is to present new strategies that can be applied towards cancer diagnostics and shed light on the metastatic process. Significant progress has been made over the last decade towards the development of approaches that enable the capture of rare circulating tumor cells (CTCs) from the blood of cancer patients and provide detailed proteomic, genetic, and phenotypic analysis. During cancer metastasis, cells may transition from an epithelial to a mesenchymal phenotype. We designed a microfluidic device that sorts CTCs into subpopulations representing different phases of epithelial to mesenchymal transition (EMT). This allows us to detect more invasive subpopulations and monitor their abundance during treatment regimes. We hypothesize that identification of CTC subpopulations can provide enhanced diagnostic information. CTCs are labeled with magnetic nanoparticles conjugated to an antibody against a cancer cell surface marker (such as epithelial cell adhesion molecule; EpCAM). Magnetically tagged CTCs are sorted into four zones of the device based on their surface level of EpCAM. The microfluidic device was used to profile low- EpCAM CTCs from metastatic castrate resistant prostate cancer patients over a defined treatment period, and towards identification of invasive cell subpopulations. Metastasis begins with the invasion of tumor cells into the extracellular environment and migration towards the blood stream. Elucidating factors which govern successful tumor cell dissemination may allow the development of therapies that can halt metastasis. We hypothesized that invasive cancer cells will selectively engage with pores of specific geometries when presented with porous micro-structures. We created 3D 20µm- tall pores of varying cross section and aspect ratios to mimic the extracellular space and to monitor the migration of breast cancer cells. We identified that breast cancer cells exhibit a pathfinding behavior when navigating through a complex arrangement of pores. Overall, the designed microdevices provide a means to identify features of invasive cancer cells using nanoparticle- assisted sorting, and migration analysis through porous structures. These approaches provide further insight into the metastatic process.

Keywords: assay
cancer
circulating tumor cells
metastasis
microdevices
migration
Advisor: Kelley, Shana O.
Dynamic Capitalisms? Understanding Patterns of Technological Specialization through an Exploration of Interfirm Interaction at International Trade Fairs

In recent years, the study of comparative capitalisms has raised important questions about the dynamic elements of capitalist diversity and the need for better explanations of institutional change. Building on this and related literatures in political economy and economic geography, this thesis explores a source of economic dynamism that has been overlooked in political science: international trade fairs. Despite their relative neglect in this field, trade fairs have long been recognized as an important promotional and sales tool. More recently, scholars have conceptualized trade fairs as critical sites through which global knowledge flows are circulated and ideas for innovation explored. From this perspective, trade fairs represent important platforms for networking, interactive learning, and knowledge exchange because they foster intense interactions among actors despite spatial boundaries. And, since trade fairs are organized according to a specific technological or industry focus, they facilitate interactions between firms from different capitalist varieties. Through the diffusion of state-of-the-art knowledge, trade fairs may serve as drivers of economic globalization, challenging the continuation of distinct capitalist varieties by enabling cross-system convergence regarding the technological specialization of firms. Yet, it is clear that countries have retained competitive advantages in specific industries and that full convergence has not taken place. Adopting a mixed-methods approach, this thesis addresses this puzzle, first, by exploring the micro-processes of search through a qualitative study. Using the garbage-can model and the “organized anarchy” concept, it finds that firms’ search processes rarely follow a linear or rational trajectory; yet, they are guided by the pre-existing production contexts and knowledge bases of their home countries. The empirical foundations of these findings are broadened through a quantitative study, which identifies different learning and search patterns between German and U.S. firms at trade fairs, largely consistent with the Varieties of Capitalism perspective. Taken together, the analysis reveals the path-dependent nature of firms’ search processes and suggests that firms from different countries are embedded in distinct paths and tend to follow their specific pathway. The thesis highlights the role of trade fairs as mediators of global economic processes and calls for greater attention to these events in political science.

Keywords: Comparative Capitalisms
Garbage-Can Model
Institutional Change
International Trade Fairs
Search Processes
Varieties of Capitalism
Advisor: Bathelt, Harald
Revenue Management in the Sharing Economy

In this thesis, we study revenue management problems in the sharing economy. In the first chapter, we study contingent stimulus policies in crowdfunding. We consider a model where backers arrive sequentially at a crowdfunding project. Upon arrival, a backer makes her pledging decision by taking into account the expected project success rate. We characterize the dynamics of a project's pledging process. To boost success, we propose and characterize three contingent stimulus policies, namely seeding, feature upgrade and limited-time offer. We show that the benefit of contingent policies is greatest in the middle of crowdfunding campaigns. Testing with the data set of Kickstarter, we obtain empirical evidence that the projects' success rates improve by 14.6% on average with updates in the middle of the campaign and when the pledging progress is lagging. In the second chapter, we study the revenue management problem with an all-or-nothing constraint. We consider a seller who would receive her rewards only when her total sales exceeds a threshold by the end of the selling period. We derive the optimal sales intensity and prove that the intensity is contingent on the sales progress and is not monotone. We analyze the deterministic heuristics and show that their performances are compromised because of the all-or-nothing constraint. We then propose a two-stage modified resolving heuristic that greatly improves the performance and has provable optimality gaps. In the third chapter, we study platform competition of on-demand matching platforms. Customers and service providers chooses the platforms according to nested logit models. We show that as the users gain access to multiple platforms, the platforms can match supply and demand more efficiently, thus increasing in the utilization of the services. However, access to multiple platforms also increases the overall attractiveness of the service. We show that if the supply side is stringent enough, the price will increase when the platforms compete on the demand side. Similarly if the demand side is stringent enough, the wage will decrease when the platforms compete on the supply side.

Keywords: Crowdfunding
On-demand matching
Revenue management
Sharing economy
Advisor: Hu, Ming