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- Genre: Academic theses
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While the COVID-19 pandemic continues to evolve, America’s nursing work force continue to work in the most challenging of circumstances. While expected to hold the fort and continue on, deep inside, they bury an unprecedented level of acute stress, anxiety and depression. Peer support groups have been posed as a possible coping behavior. This cross-sectional designed project was developed to assess the worth and feasibility of a virtual peer support group with a focus on healthcare provider wellness during a period of surge of the COVID-19 pandemic. Overwhelmed staff, technology/documentation changes and challenges, competing clinical demands, short-staffing and Zoom fatigue were identified as the limiting factors for this project’s completion within its given timeframe. These findings informed of current barriers, providing a basis for future program development to mitigate the impact of psychological distress among healthcare providers. Evolving literature on this topic supports recommendations for further study and action by individual health care providers, organizations and at the state and national levels.

Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.
To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.
This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.
This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.
This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.


This study addresses the problem of particle image segmentation by measuring the similarity between a sampled region and an adjacent region, based on Bhattacharyya distance and an image feature extraction technique that uses distribution of local binary patterns and pattern contrasts. A boundary smoothing process is developed to improve the accuracy of the segmentation. The novel particle image segmentation algorithm is tested using four different cases of particle image velocimetry (PIV) images. The obtained experimental results of segmentations provide partitioning of the objects within 10 percent error rate. Ground-truth segmentation data, which are manually segmented image from each case, are used to calculate the error rate of the segmentations.

Here, this research extends that exploratory work in an effort to determine if hfg of aqueous nanofluids can be manipulated, i.e., increased or decreased, by the addition of graphite or silver nanoparticles. Our results to date indicate that hfg can be substantially impacted, by up to ± 30% depending on the type of nanoparticle. Moreover, this dissertation reports further experiments with changing surface area based on volume fraction (0.005% to 2%) and various nanoparticle sizes to investigate the mechanisms for hfg modification in aqueous graphite and silver nanofluids. This research also investigates thermophysical properties, i.e., density and surface tension in aqueous nanofluids to support the experimental results of hfg based on the Clausius - Clapeyron equation. This theoretical investigation agrees well with the experimental results. Furthermore, this research investigates the hfg change of aqueous nanofluids with nanoscale studies in terms of melting of silver nanoparticles and hydrophobic interactions of graphite nanofluid. As a result, the entropy change due to those mechanisms could be a main cause of the changes of hfg in silver and graphite nanofluids.
Finally, applying the latent heat results of graphite and silver nanofluids to an actual solar thermal system to identify enhanced performance with a Rankine cycle is suggested to show that the tunable latent heat of vaporization in nanofluilds could be beneficial for real-world solar thermal applications with improved efficiency.



Two main strategies have emerged for integrating sustainability grand challenges. In the stand-alone course method, engineering programs establish one or two distinct courses that address sustainability grand challenges in depth. In the module method, engineering programs integrate sustainability grand challenges throughout existing courses. Neither method has been assessed in the literature.
This thesis aimed to develop sustainability modules, to create methods for evaluating the modules’ effectiveness on student cognitive and affective outcomes, to create methods for evaluating students’ cumulative sustainability knowledge, and to evaluate the stand-alone course method to integrate sustainability grand challenges into engineering curricula via active and experiential learning.
The Sustainable Metrics Module for teaching sustainability concepts and engaging and motivating diverse sets of students revealed that the activity portion of the module had the greatest impact on learning outcome retention.
The Game Design Module addressed methods for assessing student mastery of course content with student-developed games indicated that using board game design improved student performance and increased student satisfaction.
Evaluation of senior design capstone projects via novel comprehensive rubric to assess sustainability learned over students’ curriculum revealed that students’ performance is primarily driven by their instructor’s expectations. The rubric provided a universal tool for assessing students’ sustainability knowledge and could also be applied to sustainability-focused projects.
With this in mind, engineering educators should pursue modules that connect sustainability grand challenges to engineering concepts, because student performance improves and students report higher satisfaction. Instructors should utilize pedagogies that engage diverse students and impact concept retention, such as active and experiential learning. When evaluating the impact of sustainability in the curriculum, innovative assessment methods should be employed to understand student mastery and application of course concepts and the impacts that topics and experiences have on student satisfaction.

Results indicated that participants who received blended strategy training produced higher quality source-based essays than participants who received only reading comprehension, writing strategy training, or no training. Furthermore, participants who received only reading comprehension or writing strategy training did not produce higher quality source-based essays than participants in the no-training control group. Time on task was investigated as a potential explanation for the results. Neither total time on task nor practice time were predictive of group differences on source-based essay scores. Analyses further suggested that the impact of strategy training does not differ as a function of prior abilities; however, training does seem to impact the relation between prior abilities and source-based essay scores. Specifically, prior writing ability was unrelated to performance for those who received writing training (i.e., Writing Pal and blended conditions), and prior reading ability was unrelated to performance for those received the full dosage of iSTART training. Overall, the findings suggest that when taught in conjunction with one another, reading comprehension and writing strategy training transfers to source-based writing, providing a positive impact on score. Potential changes to the Writing Pal and iSTART to more closely align training with source-based writing are discussed as methods of further increasing the impact of training on source-based writing.

Objective: This research examined the effectiveness of a weight loss diet incorporating high protein pasta and breakfast cereal products as compared to a weight loss diet using conventional versions of gluten-free pasta and breakfast cereal.
Design: In a 6-week parallel-arm food trial (representing the first phase of a 12-week cross-over trial), 26 overweight and obese (Mean BMI 43.1 ± 12.4 kg/m²) participants, free of related comorbidities, were randomly assigned to the Zone diet (~29% energy intake from protein) or a control diet (~9% energy from protein). Participants were included in the trial if they satisfied the criteria for elevated risk for metabolic syndrome (top half of the TG/HDL ratios of all who were tested). Participants were instructed to eat prepared meals (total of 7 cereal packets and 14 pasta meals weekly) that included patented food technologies for the Zone diet and commercially available gluten-free rice pasta and a conventional name brand boxed cereal for the control diet. Body composition was measured with a bioelectrical impedance scale at weeks 1, and 6. Food records and diet adherence were recorded daily by the participants.
Results: Both the Zone and control diets resulted in significant weight loss (-2.9 ± 3.1 kg vs. -2.7 ± 2.6 kg respectively) over time (p = 0.03) but not between groups (p = 0.96). Although not statistically significant, the Zone diet appears to have influenced more weight loss at trial weeks 3, 4, and 5 (p = 0.46) than the control diet. The change in FFM was significant (p = 0.02) between the Zone and control groups (1.4 ± 3.6 kg vs. -0.6 ± 1.5 kg respectively) at week-6. Study adherence did not differ significantly between diet groups (p = 0.53).
Conclusions: Energy-restricted diets are effective for short-term weight loss and high protein intake appears to promote protein sparing and preservation of FFM during weight loss. The macronutrient profile of the diet does not appear to influence calorie intake, but it does appear to influence the quality of weight loss. Other measures of body composition and overall health outcomes should be examined by future studies to appropriately identify the potential health effects between these diet types.