Quantifying Barriers to Meditation as a Health Behavior: Exploratory and Confirmatory Factor Analysis of the Determinants of Meditation Practice Inventory

Although the benefits of mindfulness meditation practices have been widely documented, research data suggest that there are barriers to regularly engaging in meditation behavior. In order to explore research questions pertaining to meditation initiation and adherence, psychometrically valid scales to assess barriers to meditation practice are necessary. The aim of the present study was to explore the factor structure and construct validity of the Determinants of Meditation Practice Inventory (DMPI) (Williams et al., 2011), a perceived barriers to meditation scale. Exploratory and confirmatory factor analyses along with construct validity tests were performed on data obtained from two large, community samples. Results supported the DMPI as a valid scale assessing perceived barriers with four factors, Lack of Interest, Knowledge Concerns, Pragmatic Concerns and Sociocultural Beliefs. The present study offers a DMPI-revised scale that may be reliably used to assess attitudes and beliefs that might impede meditation behavior.

Quantifying the impacts of urban wind sheltering on the building energy consumption

Common building energy modeling approaches do not account for the influence of surrounding neighborhood on the energy consumption patterns. This thesis develops a framework to quantify the neighborhood impact on a building energy consumption based on the local wind flow. The airflow in the neighborhood is predicted using Computational Fluid Dynamics (CFD) in eight principal wind directions. The developed framework in this study benefits from wind multipliers to adjust the wind velocity encountering the target building. The input weather data transfers the adjusted wind velocities to the building energy model. In a case study, the CFD method is validated by comparing with on-site temperature measurements, and the building energy model is calibrated using utilities data. A comparison between using the adjusted and original weather data shows that the building energy consumption and air system heat gain decreased by 5% and 37%, respectively, while the cooling gain increased by 4% annually.

Quantifying the Resilience of an Urban Traffic-Electric Power Coupled System

Transportation system resilience has been the subject of several recent studies. To assess the resilience of a transportation network, however, it is essential to model its interactions with and reliance on other lifelines. In this work, a bi-level, mixed-integer, stochastic program is presented for quantifying the resilience of a coupled traffic-power network under a host of potential natural or anthropogenic hazard-impact scenarios. A two-layer network representation is employed that includes details of both systems. Interdependencies between the urban traffic and electric power distribution systems are captured through linking variables and logical constraints. The modeling approach was applied on a case study developed on a portion of the signalized traffic-power distribution system in southern Minneapolis. The results of the case study show the importance of explicitly considering interdependencies between critical infrastructures in transportation resilience estimation. The results also provide insights on lifeline performance from an alternative power perspective.