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Dept. of History, Philosophy, and Political Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1973 .Y33. Source: Masters Abstracts International, Volume: 40-07, page: . Thesis (M.A.)--University of Windsor (Canada), 1973.

Social and technical networks undergo constant evolution driven by both existing entities and newcomers. In academia, research papers are continually cited by new papers, while senior researchers integrate newly arrived junior researchers into their academic networks. Moreover, social systems can be influenced by external factors that could indirectly impact their growth patterns. For instance, systematic discrimination against certain groups in academia or managerial positions can impede their long-term growth, especially when combined with group-level preferences in hiring or adoption, as observed in our study. To address this, we introduce a network growth and adoption model where generalised preferential attachment and asymmetric mixing act as the two fundamental mechanisms of growth and adoption. We show analytically and numerically that these mechanisms can recover the empirical properties of citation and collaboration growth, as well as the inequalities observed in the growth dynamics of groups. This model can be used to investigate the effect of intervention in group mixing preferences to overcome the cumulative disparities in the group-level dynamics.

The high-temperature gas-cooled reactor pebble-bed module (HTR-PM) nuclear power plant consists of two nuclear steam supply system modules, each of which drives the steam turbine by the superheated steam flow and is fed by the heated-up water flow. The shared steam/water system induces mutual effects on normal operation conditions and transients of the nuclear power plant, which is worthy of safety concerns and intensive study. In this paper, a coupling code package was developed with the TINTE and vPower codes to understand how the HTR-PM operated. The TINTE code was used to analyze the reactor core and primary circuit, while the vPower code simulated the steam/water flow in the conventional island. Two TINTE models were built and coupled to one vPower model through the data exchange in the steam generator models. Using this code package, two typical transients were simulated by decreasing the primary flow rate or introducing the negative reactivity of one module. Important parameters, including the reactor power, the fuel temperature, and the reactor inlet and outlet helium temperatures of two modules, had been studied. The calculation results preliminarily proved that this code package can be further used to evaluate working performance of the HTR-PM.

The debate between cap-and-trade and carbon tax, two major carbon emission reduction mechanisms to deal with global warming, has been going on for years unsettled. The strategy to implement one of them or both is by far mainly addressed at the national level, and there is a need to customize the policy-making for different sectors, especially the emerging remanufacturing industry that has the great potential to reduce material and energy consumptions. Based on a closed-loop supply chain model, this study analyzes the tradeoffs between carbon tax and cap-and-trade with a series of numerical studies. While keeping carbon emissions under control, cap-and-trade demonstrates a better fit to remanufacturing: its performances on manufacturer profit, social welfare, and consumer surplus surpass carbon tax' in nine, eight, and six out of nine groups respectively. Only when the carbon quota level is too high, the cap-and-trade is possible to lose. In addition, this study examines two government-to-enterprise-subsidy strategies, direct subsidy and policy bias, and find both helpful but almost no difference in their impacts. The findings yield useful insights into the industry-wise design of carbon emission reduction mechanisms for remanufacturing and similar sectors.

Based on a longitudinal national survey, this study examines the adoption of electronic medical records (EMR) by clinics in the USA between 2004 and 2014. A trend analysis suggests that government incentive, technological breakthrough and patient-centered care push the diffusion forward. The interaction among policy, technology and practice is likely to affect the decision-making of practitioners regarding EMR adoption. This study identifies clinic-, patient- and visit-related variables from the survey, and uses them to predict EMR adoption intention and usage in each year. The explanatory power of different variables changed over time in different ways, revealing how policy, technology, and practice influence EMR adoption together. The findings yield implications for the strategies and best practices of health IT diffusion.

Based on a longitudinal national survey, this study examines the adoption of electronic medical records (EMR) by clinics in the USA between 2004 and 2014. A trend analysis suggests that government incentive, technological breakthrough and patient-centered care push the diffusion forward. The interaction among policy, technology and practice is likely to affect the decision-making of practitioners regarding EMR adoption. This study identifies clinic-, patient- and visit-related variables from the survey, and uses them to predict EMR adoption intention and usage in each year. The explanatory power of different variables changed over time in different ways, revealing how policy, technology, and practice influence EMR adoption together. The findings yield implications for the strategies and best practices of health IT diffusion.