-
Prospective Students
-
Faculty and Staff
-
Current Students
-
Alumni and Friends
Background: Current popular conceptualizations of the psychological process Repetitive Thought (RT) appear of limited accuracy due to ample construct proliferation (e.g. equating RT with rumination or worry), tautological definitions, and the construct being studied primarily in mentally disordered populations. This paper sought to unite current disparate lines of research surrounding RT, in order to illuminate and clarify the nature of RT.
Methods: Two studies were completed: First, a systematic literature review was conducted in order to develop a more comprehensive and conceptually coherent model of RT. Second, the structural validity of the model produced by the first study was empirically tested using factor analytic and multiple regression techniques.
Results: Partially Exploratory Factor Analyses revealed a strong general Repetitive Thinking factor, as well as a three-factor model that was empirically most appropriate (Intrusive Repetitive Thought, Deliberate Processing, and Self-Conscious Repetitive Thought). Additional validation analyses confirmed these findings.
Conclusions: This study contributes to our understanding of the nature of Repetitive Thought. Importantly, the three RT factors can be conceptualized as independent dimensions that are all part of a larger RT trait. The empirical and applied implications of the conceptualization of RT, as well as development of a preliminary measure of RT, are discussed.
Advancement in terahertz technologies have drawn interests in optical components suitable for the terahertz spectral range. Stereolithography, with its superior resolution, could be an efficient way of fabricating such terahertz elements with sub-wavelength scale architectures. However, stereolithographically fabricated terahertz optical elements or metamaterials have not yet been studied extensively. In this thesis, we sought to explore the terahertz optical properties of stereolithographically fabricated optics and novel metamaterials. Terahertz optical properties of materials commonly available for stereolithography have been accurately determined. Utilizing the determined properties, one-dimensional terahertz photonic crystals and defect modes within such crystals have been demonstrated for the first time through a single-step stereolithography from a single dielectric material. Mechanical tunability of the photonic bandgap and defect modes of the photonic crystals was experimentally realized. In addition, stereolithographically fabricated anisotropic metamaterial composed of slanted columnar structures have been investigated as a single layer, as well as constituent layers of one-dimensional photonic crystal structures for the first time. Off-axis parabolic reflectors have been demonstrated by metalizing a stereolithographically fabricated polymer base and by employing one-dimensional photonic crystal structure into design. In conclusion, stereolithography has been introduced as a new paradigm for fabrication of custom terahertz elements and novel metamaterials with tailored optical properties.
Stress wave propagation in granular materials subjected to dynamic loadings has attracted much attention for exploring new physical phenomena. One-dimensional (1D) granular systems, a type of artificially designed granular materials consisting of periodically aligned discrete particles, are demonstrated to produce unprecedented wave properties that are notably different from conventional engineering materials. By designing the critical characteristics of 1D granular systems, a remarkable tunability can be achieved, which yields various engineering applications. Therefore, it is of great significance to fundamentally investigate the stress wave propagation and tunability in 1D granular systems.
Firstly, the solitary wave propagation within 1D granular crystals based on composite cylinders is systematically investigated via experiments, numerical simulations, and theoretical analysis. Next, we investigate the properties of Nesterenko solitary wave supported by one-dimensional granular chains and achieve an equivalent wave transmission among various materials and dimensions. Furthermore, we develop efficient and controllable stress wave attenuation approaches by considering I. Strain-softening behaviors; II. Kirigami-based structures. Finally, we design a 1D cylindrical granular system and comprehensively investigate solitary wave tuning strategies based on the system through mass, modulus, and thickness mismatch. Results unlock the unique solitary wave tuning mechanism and provide design guidance for next-generation signal measurement and monitoring systems.
Appropriate infant and child feeding practices and balanced nutrition can significantly reduce malnutrition and can contribute to optimal physical, mental, and developmental growth of children. Childhood obesity is a major public health concern in the United States and is associated with both physical and psychological consequences and decreased health-related quality of life. Early life feeding practices and nutrients intake starting from birth to 2 years can significantly contribute to the development of obesity. This dissertation aimed to develop three manuscripts to understand the association between infant feeding practices including bottle feeding practices, initiation of added sugar and added sugar intake, and children’s BMI-for-age percentile at 36 months old among Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) participants. First manuscript examined the association between added sugar consumption at young age and BMI-for-age percentile at 36 months old among WIC participants. Second manuscript examined factors associated with initiation of added sugar among WIC participants. Third manuscript examined the association between usual daily intake of added sugar at young age and BMI-for-age percentile at 36 months old among WIC participants. Data were from the WIC Infant and Toddler Feeding Practices Study-2 (ITFPS-2). The ITFPS-2, a longitudinal study of WIC participants (mothers and their children) began in 2013. First, Cox proportional hazards model was used to identify factors associated with bottle cessation, and multivariate linear regression to examine the association between age of bottle cessation and BMI. Second, Cox proportional hazards model examined factors associated with introducing added sugar. Third, bivariate analysis was used to examine the association between usual daily intake of added sugar before age 2 years old and BMI-for-age-percentile at 36 months old. The first research study indicates about 34% of children used a bottle longer than 12 months, and 13% longer than 18 months. Bottle cessation at older ages was associated with Hispanic ethnicity, multiparity, low income, low education, higher caregiver weight, and not initiating breastfeeding, and adjusted children’s BMI-for-age percentile at age 36 months increased by 0.47 for each additional month of bottle use. The second research study indicates about 25% of children initiated added sugar at or before 7 months. Contributing factors were caregiver’s race/ethnicity, education, employment, weight status, parity, child sex, and premature birth (all p<0.05). The third research study indicates the mean added sugar intake ≤7 months, 8-13 months, and 14-24 months were 0.23 teaspoon (tsp), 3.44 tsp, and 11 tsp, respectively. Bivariate analysis indicates added sugar intake before 2 years old is associated with children’s BMI-for-age-percentile at 36 months old. These research studies indicate a need for health care advocacy programs and intervention to educate the caregivers to practice appropriate feeding practices among infants and children aged 2 or younger.
Careful control of intracellular signaling pathways plays an important role in a cell’s ability to maintain stable internal conditions in the face of an ever-changing extracellular environment. This is particularly true as it relates to the process of cellular self-eating or autophagy. Macroautophagy (herein referred to as autophagy) is a catabolic process by which unneeded or damaged cellular components are sequestered as cargo into unique double-membrane vesicles called autophagosomes which fuse to the vacuole (yeast lysosome) to be metabolized. The autophagy-related (Atg) proteins that mediate and regulate the process are evolutionarily conserved across all autophagy pathways, including starvation-induced bulk autophagy and cargo-selective autophagy pathways. The central theme of this thesis is to understand how autophagy is affected by lipids and regulatory proteins in yeast. In this thesis, we have summarized the field’s understanding of lipid homeostasis and trafficking during autophagy and autophagosome formation. Furthermore, we have extended this knowledge by discovering a clear interplay between autophagy and the SNX-BAR protein subfamily. In recent years, the SNX-BARs have been reported to have emerging roles in autophagy, however, such mechanisms of action have been primarily indirect. In this thesis, we have characterized a novel SNX-BAR protein, we have termed Vps501 and have found it directly affects autophagy which brings to light a new role of SNX-BAR proteins in autophagy regulation.
Opioid overdose deaths have increased substantially over the past fifteen years. I characterized the experience of the medical community and measured the multi-level factors influencing opioid prescribing within the context of legislation and clinical decision support interventions.
My content analysis of letters to the editor in JAMA demonstrated that physicians seek to balance pain management and the adverse effects of opioids. Physicians took ownership of their role in the epidemic but called upon the government and community to help address the issue.
My interrupted time series study revealed that legislation resulted in patients with acute musculoskeletal injury (n=12,918) having 17.7% increased frequency (p<0.001) of receiving a perception for <7 days, climbing to 77.1% of all opioid prescriptions. Physician and facility characteristics accounted for 30% and 9% of the observed variation, respectively.
A clinical decision support intervention lowered the percent of patients with chronic musculoskeletal conditions (n=1,290,746) receiving an opioid by 1.6% (p=0.0002) but had no effect on dose. Practice accounted for 24% of the variation in safe opioid prescribing scores.
Collectively, this research presents a sophisticated and nuanced understanding of the multi-level factors which influence guideline-concordant opioid prescribing. These data can inform tailored interventions and guide decision-making and policy.
Optimally modulating a vehicle's speed profile through highway, urban, and suburban environments can result in pronounced fuel savings, particularly with heavy-duty vehicles. However, existing strategies for speed profile optimization traditionally rely on aspirational and often deterministic assumptions, which cease to be accurate in the presence of real-world features such as non-deterministic traffic and actuated signalized intersections. The research in this dissertation establishes a hierarchical Green-Light Approach Speed (h-GLAS) strategy for controlling vehicles traveling through non-deterministic highway, urban, and suburban environments. The h-GLAS strategy utilizes vehicle-to-infrastructure (V2I) communication to receive information about the route's topology, speed limits, and signal phase and timing (SPaT). For suburban environments that employ semi- and fully-actuated signalized intersections, past signal timing information is used forecast the future values of the signal phase lengths. This information is used to construct a desired velocity profile to be tracked by a semi-economic model predictive controller (MPC), which computes the optimal wheel force command for the vehicle. When traveling through highway environments, the desired velocity profile represents a globally optimal dynamic program solution, computed offline before the beginning of a trip. For urban and suburban environments, however, the velocity profile is constructed to allow the vehicle to arrive at upcoming intersections when the probability of a green signal is maximized. The semi-economic MPC minimizes a quadratic objective function, which reflects a trade-off between minimizing mechanical energy expenditure and braking effort, with tracking the supplied desired velocity profile. This MPC is unable to maintain vehicle following constraints without changing its convex nature, so a command governor (CG) is located downstream to maintain vehicle-following constraints efficiently. The CG modifies the MPC's control action by the minimal amount necessary to maintain safe vehicle following. Using the simulation packages from PTV VISSIM, the h-GLAS is validated against real signal timing algorithms within a stochastic traffic environment parameterized by real-world data. Simulation results show that the h-GLAS controller is capable of significantly reducing a vehicle's fuel consumption by 16%-26% when compared to a baseline control strategy traveling through the same suburban environment.
Per- and polyfluoroalkyl substances (PFAS) are fluorinated organic compounds with broad applications in aqueous film-forming foams (AFFF) for firefighting, lubricants, waterproof and stain-resistant products. Perfluorooctanoic acid (PFOA), a legacy PFAS, is toxic and carcinogenic. Currently, PFOA is replaced by the ammonium salt of a perfluoroalkyl ether carboxylic acid known as GenX. Nevertheless, PFOA is expected to be present in the environment for an extended period after its phasing out due to its recalcitrant nature. In addition, GenX is predicted to have similar toxicity as PFOA. Various PFAS, including PFOA and GenX, have been widely detected in surface water and groundwater in the United States and worldwide. The current treatment practice for PFAS fails to provide a permanent solution and is likely to increase the risk of recontamination of surface water and groundwater.
Among various destructive methods, electrochemical mineralization, which uses electric power to transform PFAS into bicarbonate and fluoride, is a promising option. However, past studies on electrochemical mineralization of PFAS have limitations such as low PFAS mineralization and incomplete fluorine mass balance. Hence, this study proposes a sequential treatment with ion exchange to capture and concentrate PFAS in surface water and groundwater into a low volume of brine, followed by electrochemical treatment of the PFAS-containing brine. This study will focus on the electrochemical oxidation part of the treatment train and examine the treatment performance using PFOA, GenX, and AFFF waste streams as examples.
With the worldwide prevalence of obesity doubling over the past 30 years across a wide range of demographic and socioeconomic groups, the obesity epidemic is a major public health challenge today. Excessive food consumption and lack of exercise are two major contributors to obesity. In recent years, these two activities have been integrated into our daily lives together with social media. A growing body of literature delineated how social networks impact people's health-related behaviors and suggested social media has a role in affect people's obesity-related behaviors. This study aims to gain an insightful understanding of which online social factors are impacting users' obesogenic behaviors and explore computational methods to examine those behaviors using social media data.
Our work consists of three overall research aims. In the first aim, a systematic review was conducted to examine online social factors concerning obesity. A total of 1,608 studies that related to obesity and social media were collected from the three most popular electronic databases for the field. After close inspection, 50 studies were further examined and ten types of online social factors were identified within four-level social-ecological model, which was used to explain each factors' potential impact on an individual from varying levels of online social structure to user's connection to the real world. In the second aim, we learned how the local food environment influences state level obesity rate using social media data. Publicly available Yelp and MyFitnessPal data were collected via a novel approach to characterize the local food environment. A statistically significant correlation between the state's food environment and state obesity rate was observed. We further built a computational model to predict the state-level obesity rate using aforementioned data, in which we achieved a Pearson correlation of 0.791 across US states and the District of Columbia. In the third aim, we studied how a major social disrupting event, COVID-19 shutdown, affects users' dietary behavior using social media data. Tweets relating to people's dietary behavior with images from April to June of 2019, 2020, and 2021 were collected. An observational study of behavior patterns was conducted by using image classification models, visualization tools, and text analysis methods. People are found eating more healthier food during complete and partial shutdowns than before Covid-19. Results of this dissertation could help the public health agencies, policymakers, organizations and health researchers to better utilize social media to carry out obesity-related education, obesity surveillance, and develop public health policy to address this challenge.
