1925 research outputs found
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The role of climate movement organizations and consciousness raising in a plant-based food system transition
No full textThe climate crisis is a global emergency that demands drastic and unprecedented changes in all aspects of society. Thus far, transformations in the energy and transportation sectors and related industries have received the most focus, time, and resources, but the global food system is one of the biggest contributors to greenhouse gas (GHG) emissions. Without addressing GHG emissions from the food system, it is unlikely that mitigation goals can be met. One of the most impactful changes that can be made within this system is a global transition to a plant-based food system. The current animal-based food system accounts for up to 16.5% of global GHG emissions. A plant-based food system transition could reduce food sector emissions by up to 56%. Climate movement organizations are well-positioned to advocate for a plant-based food system transition at the levels of both society and governance. However, a framing analysis of climate movement organization platforms reveals that most do not promote such a transition on their platforms. Climate movement organizations can and should promote a plant-based food system transition as a way to meet their own goals and global GHG emissions reduction targets. The first paper in this thesis explores this tension. The second explores how, in attempting to promote a food system transition, climate movement organizations may find the feminist consciousness-raising (CR) group model useful. This movement tool has shown to be effective for catalyzing a vast social movement for social transformation in the past within second wave feminist movement. Positioning the normativity of animal-based diets as political ecological phenomena and the result of extensive human thought subjugation and social control, CR strategies like the CR group can be implemented by climate movement organizations to promote broad adoption of plant-based eating and mobilize society for a food system transition
The relationship of instructor-type and intervention in a first-year seminar using a closed-loop analytics model
Full text linkIn the post-COVID-19 higher education landscape, administrators must question the legacy of their programs and methods to rise up and meet not only the technological integrations that are a part of educational infrastructures, but the demands of the profession moving it beyond the twenty-first century. Since the twentieth-century, first-year seminars have been an essential and fundamental retention tool for incoming students into higher education institutions. However, with a lack of operational definitions, program uniformity, and contemporary research indicating their usefulness for today’s students, research is needed to navigate technologically enhanced pedagogies and the design principles that can and should be replicated. This study examined the data from a closed-loop learning analytics model in a first-year seminar to identify the relationship between instructor-type and the timing of intervention when predicting for the real-time student success indicator of the course grade. Results from this study have both practical and research implications that indicate further efforts are needed to understand what elements of this traditional model should be moved into the classrooms serving students today versus those that have not been previously highlighted as essential for success
Multiwavelength observations of Jupiter Trojans and related primitive asteroid populations
Full text linkThe distribution of small Solar System bodies preserves a record of both initial conditions within the Solar nebula as well as the subsequent orbital evolution of planetary bodies. As they have undergone little geothermal evolution since their formation, primitive asteroids, including D- & P-type asteroids in the Main Belt and Jupiter Trojan clouds, represent an important reservoir of information about the history of the Solar System. The unique gravitational relationship between Jupiter and its Trojan asteroids closely ties their orbital migration histories together. Similarly, the distribution of D- & P-type asteroids within the Main Belt reveals the extent of delivery of volatile outer Solar System materials to the inner Solar System.
Understanding both these processes is critical to telling the story of how our planetary system came to be. Astronomers use spectroscopy as a tool to understand small bodies on a population level. The characteristic spectral features of asteroids reveal their compositions, and in turn, their origins. Much of asteroid spectroscopy is conducted in the visible and near-infrared (VNIR) due to its accessibility to ground-based telescopes. However, D- & P-type asteroids are red and spectrally featureless in the VNIR region, providing few constraints on the compositional makeup of these critical populations. To address this lack of constraints, I present three spectroscopic investigations of primitive asteroids in the Main Belt and Trojan clouds from the near-ultraviolet to the mid-infrared. Integrating ground-based, space-based, and airborne observations, I present analyses of the spectra of D- & P-type asteroids throughout the Solar System. In the ultraviolet, I use the Hubble Space Telescope to observe a new spectral feature of the Jupiter Trojans, an increase in reflectance shortwards of 0.35 µm. I use Hapke optical modeling to derive compositional constraints based on this new spectral feature and demonstrate that Rayleigh scattering from submicroscopic opaques, including iron and carbon, can explain this increase in UV reflectance. In the mid-infrared, I combine observations from the Stratospheric Observatory for Infrared Astronomy (SOFIA) and the Spitzer
Space Telescope to parameterize the 10- and 20-µm silicate emission feature of Main Belt D- and P-type asteroids, comparing the appearance of this feature in Main Belt asteroids to its appearance in literature spectra of the Jupiter Trojans. I show that asteroids that otherwise appear similar in the VNIR region show a diversity of spectral features in the mid-infrared. In the VNIR, I use the Lowell Discovery Telescope and the NASA Infrared Telescope Facility to search for steeply red-sloped primitive asteroids in the Main Belt. I identify red-sloped asteroids and show that subtle differences in the VNIR spectra of Main Belt red-sloped asteroids suggest multiple sub-populations of red-sloped asteroids are present in the Main Belt
Faculty perceptions of online teaching and learning: an interpretive phenomenological analysis
Full text linkThis qualitative phenomenological study was an exploration of the lived experiences and perceptions of five full-time faculty members and their perceptions of online teaching and learning as a result of the COVID-19 pandemic. Semistructured interviews elicited information to describe faculty perceptions of online teaching and learning and further explore the advantages, disadvantages, and challenges of online teaching and learning. With a two-step deductive and inductive coding process grounded in transformational learning theory, this study showed how faculty moved through transformational learning stages and indicated the salient themes associated with faculty perceptions
Evolving job demands: how elementary school principals take care of themselves to support their resiliency and retention
Full text linkThe purpose of this qualitative transcendental phenomenological study was to examine the lived experiences of female elementary school principals as they navigate workplace stress and personal well-being. Work intensification and subsequent stressors for school principals are not a recent phenomenon; however, the impact of the COVID-19 pandemic on students and staff coupled with the pandemic-era national political climate have created an unprecedented context for educational leaders. There is a lack of research concerning changes in principal stress, including female school leaders who are more susceptible to job-related stress, and resiliency after a multi-year global pandemic. The aim was to contribute to the research to support principal well-being and retention. Participants included eight female elementary school principals within two districts located in the Phoenix metropolitan area. This qualitative study captured data from participants through a preliminary demographic survey and one-to-one interviews. Interviews were semi-structured with questions aligned to the three research questions guiding this study. Research question 1 addressed principals experienced with job-related stress over time, including during the COVID-19 pandemic. Findings revealed participant well-being is being negatively impacted by job-related stress, and this stress has worsened since the onset of the COVID-19 pandemic. Stressors of staffing and balancing teacher well-being, student discipline, parents, district initiatives, rebounding from the pandemic, and personal tragedies all surfaced as themes. Job-related stress was found to negatively impact participants within and outside of the workplace through moods, behaviors, feelings of isolation, impacts to relationships with loved ones, and inability to disengage. Research question 2 addressed the coping strategies used by participants to mitigate job-related stress. Participants identified multiple ways they cope with the stress they experience which included the themes of establishing boundaries, time with family and friends, exercise, and reflection/mindsets. Research question 3 addressed whether stress-coping experiences influenced their desire to remain in their role. While the majority of participants described their deep commitment to the educational field, they shared how their stress-coping strategies are not enough to support a desire to remain in their principal roles long-term
Enrollment management: public school district leaders' experiences, and the effects of community trust in leaders
Full text linkThe purpose of this study was to examine enrollment management needs and potential processes in traditional public preschool through 12th grade school districts. This study allowed school districts to examine their own individual unique enrollment management needs and potential processes for moving forward in making equitable decisions for all students while also being fiscally responsible. Trust with various stakeholders is an essential component when districts make enrollment management decisions which can affect the various community stakeholders in different ways.
This case study utilized a mixed methods approach which involved collecting, analyzing, and summarizing both qualitative and quantitative data using descriptive data analysis. Participants included Arizona superintendents who completed a survey and five superintendents from those who completed the survey were selected to be interviewed for a more in depth look at enrollment management within their own school district.
Research Question 1 addressed key components of effective PreK-12 enrollment management, as described by participants. This included many things but most often was space utilization, magnet or specialized programs, and boundaries. Utilizing an external service provider can assist superintendents in collecting and analyzing a myriad of relevant data.
Research Question 2 addressed how district leaders use enrollment management to determine the best use of resources. Understanding a district’s space utilization is important in determining enrollment management steps. Additional funding sources, such as voter approved overrides and bonds, can be vital to a district determining what they realistically can or can’t do in regards to specialized programs, keeping schools updated, renovated, and if in a growing district even building new schools. Communication with stakeholders is vitally important when looking at various enrollment management initiatives.
Research Question 3 addressed how enrollment management was used to ensure educational accessibility for all students. School choice including open enrollment is prevalent in Arizona. Each school district is affected by school choice and open enrollment either positively or negatively based on the number of students registered. Superintendents reported educational accessibility for all students is an important component of making enrollment management decisions.
Research Question 4 addressed how trust affects school districts in making enrollment management decisions. Superintendents’ relationships with various stakeholders determines the level of trust found when making potentially volatile enrollment management decisions. Being transparent, humble, and willing to admit mistakes goes a long way in building trust. Knowing who the movers and shakers are in a district is vital to building trust with a wide range of stakeholders.
Enrollment management is complex and what components a district will focus on will be suited to the particular needs of the school district
Paleoenvironments and geochronology of the Eocene Wagon Bed Formation, central Wyoming
Full text linkThe subduction of an oceanic plateau and consequent shallow subduction of the Farallon plate beneath North America have long been proposed to explain the contractile deformation that led to the formation of the Rocky Mountains and associated basins across a craton. However, questions remain about the extent of emplacement, timing of slab removal, and its influence on the land surface above. In this study, I investigate the Eocene Wagon Bed Formation in central Wyoming to better understand the relationship between its lacustrine deposits and late-stage Laramide tectonics and magmatism, as well as to provide a comprehensive record of deposition in the region during the Eocene. Eight new 40Ar/39Ar radioisotopic dates for tuff beds and volcaniclastic sandstone reveal the Wagon Bed Formation was likely deposited between 50 and 35 Ma, on far longer timescales than previously recognized, and includes a ~5 Ma unconformity in the middle. Geochronology at Lysite Mountain suggest deposition occurred only from 50 to ~43 Ma. The formation shows significant spatial and temporal variation along the Beaver Rim, with lacustrine paleoenvironments confined to the west of the Conant Creek anticline, and well-drained volcaniclastic-rich alluvial environments to the east. Similar lacustrine lithofacies to the Beaver Rim area also exist in the north at Lysite Mountain. Stable isotope data from carbonates and volcanic glass suggest the paleolakes in both locations were likely closed or semi-closed, consistent with saline lake indicators such as stromatolites, oil shales, and authigenic zeolites. Deposition of the Wagon Bed Formation suggests the collapse of the Granite Mountains began by at least 45 Ma, 30 million years earlier than currently documented. The removal of compressional stresses during rollback caused the Granite Mountains, a rootless uplift, to extend along preexisting thrust faults or create new normal faults. Evidence of drainage disruption, lacustrine sequences, an increase in volcaniclastic material, unconformities, and extension indicate that the Wagon Bed Formation could record the surficial expression of Farallon plate removal on the overriding North American plate
The effects of colorblind racial socialization on perceptions of black criminality
Full text linkCurrent literature on racial socialization frequently examines its role in promoting positive intercultural relations and minimizing racial stereotypes. More recently, the effects of different forms of racial socialization, such as colorblind and color-conscious racial socialization, have also been examined. However, no existing literature on racial socialization considers how different racial socialization practices can influence the development of racial stereotypes, such as the perception of black criminality. This thesis thus explores this relationship. Using a quantitative research design, this thesis randomly selected a sample of undergraduate students at Northern Arizona University’s Flagstaff Mountain Campus to complete an online survey. Questions pertained to the frequency of parental racial socialization behaviors, individual colorblind racial attitudes, and estimations of black criminality, and it was hypothesized that individuals who experienced more instances of colorblind racial socialization were more likely to have greater perceptions of black criminality. Results generally supported this hypothesis, suggesting that colorblind racial socialization operates indirectly through colorblind racial attitudes to affect perceptions of black criminality. The importance of these results are explored with regard to prior literature and theory, and policy implications, including the need for increased awareness of racial biases, are considered
Understanding last-mile package delivery in urban areas and the inclusion of autonomous technology
Full text linkThe demand for same-day package delivery in the United States is growing and has fostered the development of new, technologically advanced delivery systems. Given the rate that humanity widely adopts new technologies it is important to explore these emerging delivery methods, including Sidewalk Autonomous Delivery Robots (SADRs) and App-Based Food Delivery (ABFD) systems, to gain an understanding of their potential impacts on urban transportation networks. By assessing consumer behaviors and characteristics in areas where these services currently operate, it is possible to predict where stress will be observed in other urban environments to aid planners in directing their efforts accordingly. This thesis explores this topic and highlights the importance of understanding how SADRs and ABFD services operate in multimodal environments and generates predictors of which populations are likely to use them
Physics informed neural networks to solve forward and inverse fluid flow and heat transfer problems
No full textThis dissertation proposes novel approaches to address challenges in solving fluid flow and transport problems in heterogeneous systems using deep learning methods.The first approach is a multi-fidelity modeling approach that combines data generated by a low-fidelity computational fluid dynamics (CFD) solution strategy and data-free physics- informed neural networks (PINN) to obtain improved accuracy. High-fidelity models of multiphysics fluid flow processes are often computationally expensive. On the other hand, less accurate low-fidelity models could be efficiently executed to provide an approximation to the solution. Multi-fidelity approaches combine high-fidelity and low-fidelity data and/or models to obtain a desirable balance between computational efficiency and accuracy. In the proposed approach, transfer learning based on low-fidelity CFD data is used to initial- ize PINN, which is then used to obtain the final results without any high-fidelity training data. Several partial differential equations are solved to predict velocity and temperature in different fluid flow, heat transfer, and porous media transport problems. The proposed approach significantly improves the accuracy of low-fidelity CFD data and also improves the convergence speed and accuracy of PINN.
The second approach is an ensemble PINN (ePINN) method that is proposed to solve the uniqueness issue of inverse problems. In inverse modeling, measurement data are used to estimate unknown parameters that vary in space. However, due to the spatial variability of these unknown parameters in heterogeneous systems (e.g., permeability or diffusivity), the inverse problem is ill-posed and infinite solutions are possible. PINN has become a popular approach for solving inverse problems but is sensitive to hyperparameters and can produce unrealistic patterns. The ePINN approach uses an ensemble of parallel neural networks that are initialized with a meaningful pattern of the unknown parameter. These parallel networks provide a basis that is fed into a main neural network that is trained using PINN. It is shown that an appropriately selected set of patterns can guide PINN in producing more realistic results that are relevant to the problem of interest. The proposed ePINN approach increases the accuracy in inverse problems and mitigates the challenges associated with non-uniqueness.
The third approach is a novel method called ensemble deep operator neural network (eDeepONet), which is designed to solve the solution operators of partial differential equa- tions (PDEs) using deep neural networks. eDeepONet involves training multiple sub-DeepONets on smaller subsets of the dataset, which are then combined in a fully connected neural network to predict the final solution. eDeepONet reduces the complexity of the training process, improves convergence, and provides more accurate solutions compared to the tra- ditional DeepONet approach. Additionally, eDeepONet is designed to handle parametric PDE equations and does not require explicit knowledge of the PDE equation or its bound- ary conditions, making it more flexible and applicable in a wider range of applications. The effectiveness of eDeepONet in enhancing prediction accuracy and improving convergence is demonstrated on a 2D diffusion problem.
Overall, the proposed approaches demonstrate the potential of deep learning methods in solving challenging fluid flow and transport problems in homogeneous and heterogeneous systems. The multi-fidelity approach improves the accuracy of low-fidelity data and reduces computational cost. The ePINN approach mitigates the challenges associated with non- uniqueness in inverse problems. The eDeepONet approach reduces the complexity of the training process, improves convergence, and provides more accurate solutions for PDEs. These advances in deep learning methods have the potential to revolutionize our ability to model and predict fluid flow and transport in a wide range of applications