This thesis first examines the history and contemporary landscape of school mental health, offering evidence for schools as an essential component of the child and adolescent system of care. It then provides contemporary discussion around the importance of design in public administration, as well as analyzes the current design model of school-based mental health services, including key actors, normative assumptions, and underlying conceptual models to demonstrate the outdated presumptions that have led to a model that is not designed to adapt to the unique needs of students, especially after the COVID-19 pandemic. Building on contemporary theory of design in public administration, I argue that the largely fragmented, decentralized, bureaucratic, complex, and underdeveloped design of school-based mental health services mainly developed in the 1970s and 1980s has reached its limits and cannot adapt to new societal variables. Lastly, I discuss said limitations of this model to argue for a conceptual and practical re-design of the current system of school-based mental health systems in the United States.

Traumatic brain injury (TBI), a neurological condition that negatively affects neural capabilities, occurs when a blunt trauma impacts the head. Following the initial injury that immediately impacts neural cell function and survival, a series of secondary injury events lead to substantial sustained inflammation for weeks to years post-injury. To develop TBI treatments that may stimulate regenerative processes, a novel drug delivery system that efficiently delivers the appropriate drug/payload to injured tissue is crucial. Hyaluronic acid (HA) hydrogels are attractive when developing a biomaterial for tissue reparation and regeneration. HA is a natural polymer with physicochemical properties that can be tuned to match the properties of the extracellular matrix (ECM) of the many tissues including the central nervous system (CNS). Here, the project objective was to develop a HA hydrogel system for local delivery of a biological payload; this objective was completed by employing a composite system with two parts. The first part is an injectable, shear-thinning bulk hydrogel, and the second is microgels for loading biological payloads. The bulk hydrogel was composed of cyclodextrin modified HA (Cd-HA) and adamantane modified HA (Ad-HA) that give rise to guest-host interactions that facilitate physical crosslinking. The microgel, composed of norbornene-HA (Nor-HA) and sulfated-HA, crosslink via chemical crosslinks upon activation of a UV photoinitiator. The sulfated-HA microgels facilitate loading of biological payloads by mimicking heparin binding sites via the conjugated sulfated group. Neuregulin I, an epidermal growth factor with neuroprotective properties, is one such protein with a heparin binding domain that may be retained in the sulfated-HA microgels. Specifically, the project focused on mechanical testing of this composite microgel/hydrogel system and also developing protein affinity assays.

In vitro embryogenesis is a revolutionary technology were researchers are able to culture stem cells, currently from mice, and differentiate the culture into an embryo showing key developmental characteristics. This technology has extensive medical benefits through creating a collection of genetically identical tissues and organs from which patients can receive treatment options. However, there are significant ethical objections to growing an embryo simply to destroy it and take its tissues and organs. Using ethical discussions of in vitro fertilization and abortion ethics, I was able to develop a framework to begin to solve these ethical discussions by identifying several physiologic reductions, which instead make a reservoir of tissue rather than a rational being.

We implemented the well-known Ising model in one dimension as a computer program and simulated its behavior with four algorithms: (i) the seminal Metropolis algorithm; (ii) the microcanonical algorithm described by Creutz in 1983; (iii) a variation on Creutz’s time-reversible algorithm allowing for bonds between spins to change dynamically; and (iv) a combination of the latter two algorithms in a manner reflecting the different timescales on which these two processes occur (“freezing” the bonds in place for part of the simulation). All variations on Creutz’s algorithm were symmetrical in time, and thus reversible. The first three algorithms all favored low-energy states of the spin lattice and generated the Boltzmann energy distribution after reaching thermal equilibrium, as expected, while the last algorithm broke from the Boltzmann distribution while the bonds were “frozen.” The interpretation of this result as a net increase to the system’s total entropy is consistent with the second law of thermodynamics, which leads to the relationship between maximum entropy and the Boltzmann distribution.

To mitigate climate change, carbon needs to be removed from the atmosphere and stored for thousands of years. Currently, carbon removal and storage are voluntarily procured, and longevity of storage is inconsistently defined and regulated. Clauses can be added to procurement contracts to require long-term management and increase the durability of storage. Well-designed and properly enforced contracts can pave the way to future regulation for long-term carbon management.

This paper presents a comprehensive review of current advances and challenges in the field of bone tissue engineering. A systematic review of the literature was conducted to identify recent developments in biomaterials, scaffold design, cell sources, and growth factors for bone tissue engineering applications. Based on this review, an experimental proposal is presented for the development of porous composite biomaterials that may enhance bone regeneration, which consist of hybrid amyloid/spidroin fibers combined with a bioactive ceramic matrix. An iterative design process of modeling and simulation, production, and characterization of both the fibers and the composite material is proposed. A modeling and simulation approach is also presented for unidirectional fiber composite biomaterials using 2-point correlation functions, finite element simulations, and machine learning. This approach was demonstrated to enable the efficient and accurate prediction of the effective Young’s modulus of candidate composite biomaterials, which can inform the design of optimized materials for bone tissue engineering applications. The proposed experimental and simulation approaches have the potential to address current challenges and lead to the development of novel composite biomaterials that can augment the current technologies in the field of bone tissue engineering.

Many would contend that the United States healthcare system should be moving towards a state of health equity. Here, every individual is not disadvantaged from achieving their true health potential. However, a variety of barriers currently exist that restrict individuals across the country from attaining equitable health outcomes; one of these is the social determinants of health (SDOH). The SDOH are non-medical factors that influence the health outcomes of an individual such as air pollution, food insecurity, and transportation accessibility. Each of these factors can influence the critical illnesses and health outcomes of individuals and, in turn, diminish the level of health equity in affected areas. Further, the SDOH have a strong correlation with lower levels of health outcomes such as life expectancy, physical health, and mental health. Despite having influenced the United States health care system for decades, the industry has only begun to address its influences within the past few years. Through exploration between the associations of the SDOH and health outcomes, programming and policy-making can begin to address the barrier to health equity that the SDOH create.

Math homework is a highly debated topic within the middle school education field. Teachers, parents, and students all have differing opinions on what the ideal math homework assignment is and how it promotes academic achievement. This study was intended for discovering what the optimal middle school math homework assignment looks like, how teachers can best follow-up on the assignment, and the most beneficial quantity and frequency of homework. Currently, teachers need more distinct guidelines when designing homework assignments. Students in Barrett, The Honors College, at Arizona State University were asked a series of questions about the type, length, and follow-up practices of their homework assignments and how they felt about them. It was found that students who like math are generally highly motivated in the subject. Most often, students are given short but frequent practice homework assignments, which they find to be most helpful, and they appreciate when teachers review the steps and solutions to the assignments in class. These results should allow educators to better align their math homework assignments with practices that students find to be helpful and necessary.

Visualizations can be an incredibly powerful tool for communicating data. Data visualizations can summarize large data sets into one view, allow for easy comparisons between variables, and show trends or relationships in data that cannot be seen by looking at the raw data. Empirical information and by extension data visualizations are often seen as objective and honest. Unfortunately, data visualizations are susceptible to errors that may make them misleading. When visualizations are made for public audiences that do not have the statistical training or subject matter expertise to identify misleading or misrepresented data, these errors can have very negative effects. There is a good deal of research on how best to create guidelines for creating or systems for evaluating data visualizations. Many of the existing guidelines have contradicting approaches to designing visuals or they stress that best practices depend on the context. The goal of this work is to define the guidelines for making visualizations in the context of a public audience and show how context-specific guidelines can be used to effectively evaluate and critique visualizations. The guidelines created here are a starting point to show that there is a need for best practices that are specific to public media. Data visualization for the public lies at the intersection of statistics, graphic design, journalism, cognitive science, and rhetoric. Because of this, future conversations to create guidelines should include representatives of all these fields.