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This thesis investigates the effects of village economic wealth and economic autonomy on the authoritarian control of local government over village elections in China. With new data - qualitative evidence and quantitative data collected from the extensive fieldtrips to a county in Guangdong Province, this study finds that given that village elections operate within China’s one party authoritarian regime and the official purpose of the elections is to solve the grassroots governance crisis, local government have the incentive to control the elections in their favour, that is, to have incumbents and/or party members elected. Using the election of party members to the village committee chairman position and the re-election of incumbent chairmen as proxies for the inclusiveness and contestation dimensions of village elections, this study demonstrates that collective village wealth triggers fierce electoral competition, as collective village wealth represents the lucrative benefits candidates can obtain from holding the office. However, the success of authoritarian control hinges on village economic autonomy - the opportunities for economic development beyond the control of local government. If economic resources are controlled by local government, economic development might strengthen the capacity of local government to control the elections in their favour. Even if opponents win the elections, they are inclined to be co-opted by the local government - becoming party members, because their economic gain and maintenance of power are affected by the authoritarian local government control over economic resources. In most villages in the sample, authoritarian control prevails in village elections. The findings of this thesis suggest that until now the elections have been maintained within the boundary of the CCP’s authoritarian governance. In rural China, for elections to serve the function of promoting democracy and fostering checks and balances of power - neither manipulation by the local government nor manipulation by rich opponents - the key lies in the economic empowerment of villagers.

Dental caries and periodontal disease affect billions of people annually with a global prevalence estimated at 35% and 11%, respectively. Oral biofilms that develop on tooth surfaces and within gingival crevices are a major risk factor. Disease prevention efforts are focused on controlling the overgrowth of biofilms by removal (e.g., toothbrushing), antimicrobial-containing mouth rinses, and dentifrices. A number of laboratory (in vitro) models of biofilms are used to understand how biofilms develop and their response to mouth rinses and dentifrices. However, there are two major limitations to currently available in vitro biofilm model systems. First, there is no biofilm model system validated for the development of representative dental plaque biofilms. Second, there is no standard approach to analyze biofilm images. Current techniques rely on thresholding algorithms that are not designed for fluorescent images. Combined, these limitations can lead to differences in quantification of biofilm outcomes and thus raise questions regarding the relevance of the model system to the “real-world”. This dissertation seeks to bridge the gap between current laboratory techniques and software algorithms and provide investigators additional tools to conduct in vitro oral biofilm studies. First, a distillation of model systems relevant to modern in vitro oral biofilm research is provided. Second, we adapted one of these described model systems, the 24-well BiofluxTM to reproducibly grow multi-species dental biofilms. An objective imaging strategy was further developed to capture all biofilm architectural features. Before analyzing biofilm images, a novel thresholding algorithm, the biovolume elasticity method (BEM), was developed to threshold fluorescent signal. Finally, a software package called Biofilm Architecture Inference Tool (BAIT) was built and evaluated to measure core architectural features of biofilms. In summary, this dissertation describes the modification of a 24-well Bioflux system that facilitates the reproducible development of biofilms. For better visualization and quantification of in vitro biofilms, a novel thresholding algorithm was described. Finally, a software package integrating the BEM thresholding method was developed to measure architectural outcomes. The work presented here represents the outcome of a combinatorial approach to redefine techniques to study oral biofilms, and may also be relevant to the study of biofilms that exist outside the oral cavity.

We study the multi-period container leasing and load acceptance problem in intermodal freight transportation, where the container capacity could be replenished before allocated to load orders with different profit levels. The container leasing decision is exogenously determined by the initial container inventory left unused from last period and the returned containers in the current period. The load acceptance decision involves trade-offs between accepting the order now or reserve the container for potential high profit level order in the future. Our objective is to characterize the optimal policies in order to maximize the total profit. The two-stage sequential decision problem is formulated as a stochastic dynamic programming problem. We show the optimal leasing quantity follows a base-stock policy and the optimal allocation for different class of demand follows a rationing policy. We further study the impact of demand variability on the optimal policy. Given stochastically higher demand in the future, both total profit and marginal value increase. Such change in demand also results in a higher leasing threshold and a higher rationing level for each demand class.