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Energy Efficient Diamond LEED-Certified Data Centers
Get PDFData centers are critical infrastructures that consume over 40 times the energy of typical office buildings. The transition from onsite to online work environments was propelled initially by the COVID-19 pandemic and evolving artificial intelligence technologies, which have significantly increased the demand for data center growth. The surge in computing load has led to increasing energy consumption within data centers. Northern Virginia, home to the world's largest data center cluster, faces significant energy and environmental sustainability challenges due to increased computing load and energy usage.
Leadership in Energy and Environmental Design (LEED) is a globally recognized rating system that promotes environmentally friendly design, construction, and operation. When applied to buildings over the project's lifecycle, the LEED rating system is superior in energy efficiency compared to code minimum standards, resulting in energy savings over the building's lifecycle. Data center owners typically pursue LEED certification, anticipating that these long-term energy savings will offset the higher initial capital cost in a reasonable payback period. The current LEED standard needs to be evaluated to help data center owners reach new sustainability and energy efficient goals. In this thesis, an energy model was designed to evaluate the existing Data Center LEED standards and identify critical areas for improvement and validate the Diamond LEED Certification. This advanced standard is tailored for data centers to meet heightened energy efficiency and sustainability objectives, resulting in documentable energy savings. A use case for energy-efficient and sustainable data centers validates the Diamond LEED Certification
Partisans of the Old Republic: Right-Wing Opposition to U.S. Foreign Policy
Get PDFThis dissertation will advance the argument that right-wing noninterventionism emerged from a broader tradition of anti-imperialism and remained a persistent force within American conservative politics throughout the 20th century, albeit politically constrained and culturally isolated by the sociopolitical trends of postwar America. Unlike other treatments of the topic, this dissertation will begin in the earliest days of an organized and continuous noninterventionism that emerged in response to the rise of American power abroad at the turn of the 20th century. It will trace these lines of proto-conservative critique through what was once a broad political response to an assertive American foreign policy, arguing that what became known as a "right-wing" perspective on America's role in the world was rendered as such by the interplay of post-New Deal American politics and their relationship with events overseas. This dissertation is grounded in two bodies of primary source material, one congressional and another drawn from conservative media. While political histories of noninterventionism often focus on the affairs of the presidency and the cultural forces that animated them, this study shifts its political gaze towards Capitol Hill. The analysis of political materials in this study relies on a conventional close reading of traditional primary sources available through the Congressional Record and a variety of traditional sources such as op-eds, campaign ads, personal correspondence, and speeches. This dissertation also employs original computational analysis of congressional voting records and demographic data associated with members of Congress. This computational analysis draws on a dataset of almost one million voting observations from 1935 until 1996, and it disaggregates American foreign policy into its constituent parts: military, diplomatic, and foreign aid policy. This analysis reveals wide fissures in the Cold War consensus, making a case for the political staying power of the noninterventionist right throughout the early Cold War. By focusing on Congress and using this unique computational analysis, this study uncovers continuities in noninterventionist thinking and the longevity of its political presence despite the U.S. government's drive toward global dominance, continuities overlooked by earlier scholarship. This dissertation promises to provide a historical context for current events that have baffled commentators and scholars alike: the alleged and inexplicable return of "isolationism" to conservative American politics. The findings of this dissertation, coupled with our current era of discord, make the assertive, interventionist, or universalistic iterations of a conservative foreign policy look like aberrations rather than norms. Far from being dogmatic, often a synonym for conservatism, the broader landscape of the American right's foreign policy has been remarkably dynamic and contentious for a century
BRAIN CONNECTIVITY NETWORK PREDICTION USING DEEP LEARNING FOR GRAPH TRANSFORMATION
No full textThe recent surge of research into Graph Neural Networks (GNNs) has come a long way to approach problems which require structured predictions for “translating” an input graph into a corresponding output graph. Although successful in many applications, conventional GNNs are only able to deal with node translation problems to predict the node attributes or node category of the target graph. In many practical scenarios, node-edge co-transformation is required where both nodes and edges can change during translation process. Characterizing the underlying mechanism of graph topological evolution from a source graph to a target graph has been also addressed by spectral based approaches which are built on the spectral evolution model. The growth of large networks is analyzed by studying the changes in the spectral characteristics of the graph. Motivated by the evolution and transformation of brain connectivity network, my research goal is to develop an end-to end graph translation framework that can optimally handle the change in graph topology (novel technique), and apply that to the real-world domain specific task of brain connectivity network translation problem, such as structural to functional connectivity translation. Despite the rapidly-growing research on graph translation topic, in many applications, these are generally focused on either linear models or computational models that rely heavily on heuristics and simple assumptions. However, depending on the domain, while the topology changes, the relationship could be highly-nonlinear, complex, and contain considerable randomness. Beyond merely doing transformation and prediction, it is also interesting and important to figure out which subgraphs in the input graph majorly influence which subgraphs in the output. Interpretable models that can probe the data automatically and find candidate pairs of input and output subgraphs with strong correlation, are in urgent demand. Additionally, research on GNN explainability on how to generate explanations and importantly how to adjust the model to generate more accurate explanations is becoming more critical. Unlike local explanation models which explain the model prediction per input sample, global explanation techniques aim at providing general insights and high-level understanding of the predictions of a deep graph model. Specifically, they investigate what input graph patterns can lead to a certain GNN behavior or maximize the predicted probability for a certain class and use such graph patterns to explain the class. This is essential in many real-world critical applications and can substantially increase human trust in GNNs’ prediction ability. To address these challenges, my research plan is mainly 3-fold: 1) develop a novel framework for graph translation which can model the change in graph topology, and is capable of learning the stochasticity; 2) propose new post-hoc explainer of our framework that can identify which subgraphs in input strongly influence which subgraphs in output and apply that to the structural to functional connectivity mapping problem which is built upon our proposed framework; 3) design a global GNN Explanation Supervision (GNES) framework that can improve the reasonability of the generated explanations in a global manner, while still keep or even improve the backbone GNNs model performance
Analyzing the Role of Land-Atmosphere Coupling Sensitivity and Subgrid Spatial Heterogeneity in Earth System Models
Get PDFCloud formation, distribution, and other properties may be sensitive to heterogeneous surfaces depending on the strength and location of such heterogeneities and the background atmospheric state. This may drive differences in the cloud population depending on which part of the domain one is located. This may also lead to mesoscale circulations, which may strengthen or weaken this effect. Currently, climate models act on scales (~100 km) that are too large to explicitly represent these processes, which are strongest at smaller scales (around 5-40 km). Therefore, sub-grid scale (SGS) heterogeneity is neglected, and any predictability and model fidelity it may provide is lost. In this dissertation, I analyze these land-atmosphere (L-A) interactions with two new research studies.We first introduce a novel method for diagnosing land-atmosphere coupling sensitivity on the subdaily timescale. This study defines a new metric, called the coupling sensitivity score (CSS), which uses an ensemble of single-column model runs, each with varying, prescribed surface flux conditions used as a proxy for SGS heterogeneity, and driven by observationally-constrained large-scale forcing data. The CSS can diagnose both positive [increasing cloud with wetter/cooler surface] and negative [increasing cloud with drier/warmer surface] L-A coupling sensitivity. Over the Southern Great Plains (SGP), we show that depending on the large-scale atmospheric state, strong positive or negative L-A feedback behavior may be preferred. Using the CSS this way helps to gain a better first-order understanding of L-A coupling behavior when in the presence of large variations in land surface conditions. In the second study, we aim to measure how well the Community Earth System Model (CESM) parameterizes SGS heterogeneity and its effect on a given model grid cell. To do this, we demonstrate a new application of the relative entropy, a metric from information theory. The relative entropy, which measures the similarity between probability density functions (PDFs), is used to measure the fidelity of statistical SGS spatial PDFs of atmospheric properties, which are parameterized within CESM, when they are compared to more realistic spatial distributions simulated by the Weather Research Forecasting – Large-Eddy Simulation (WRF-LES) model. We test the parameterized spatial distributions under four separate parameterization configurations, testing two versions each of the shallow convection/turbulence scheme and the coupling scheme. With this technique, we show that a new, augmented version of the shallow convection/turbulence scheme, CLUBB+MF, marginally outperforms its default version, CLUBB when using the WRF-LES simulations as a target. The methodologies from these two studies are also applied to two other locations, each with a different hydroclimate than the SGP: one with much higher moisture availability in the Amazon tropical rainforest, and one in the semi-arid north central region of Argentina. Analyzing these new hydroclimates shows that both the CSS metric and our relative entropy method have generable applicability outside of the SGP, and may be used to further understand L-A coupling behavior in the presence of SGS heterogeneity and how we may improve its simulation in today’s state-of-the-art earth system models
“In Our Own Rightful Territory”: Dakota Mobility, Diplomacy, and Belonging in Mni Sota Makoce after the US-Dakota War
Get PDFIn the years following the US-Dakota War (1862), Minnesotan settlers, militiamen, and the US Army pushed Dakota people (Mdewakanton, Sisseton, Wahpeton, and Wahpekute) west and north from their Minnesota homelands. Throughout this diaspora Dakota people instilled and reinforced a broader assertion of their homelands, Mni Sota Makoce, which stretched across the Great Plains in well into the Canadian prairies. Whereas many histories cast the US-Dakota War as the demise of Dakota people in Minnesota, a spatial approach towards their diasporic movement offers another view of their survival and resistance. Indeed, many Dakota people who fled were chased by the US Army, forced into prison camps like Fort Snelling, or confined onto reservations like Crow Creek. Others found safety by crossing the US-Canadian border, a fluid but hardening boundary that separated US and Canadian jurisdictions since its creation from the 1783 Treaty of Paris and reestablishment through the 1846 Oregon Treaty. Within a larger historical context of settler nations seeking to confine all Indigenous peoples, Dakota people in diaspora used mobility across their extended homelands to spark a transnational confrontation over their communal rights and sovereignty. This dissertation approaches mobility as an analytical lens to better encapsulate the tumultuous decades that followed the US-Dakota War. Whereas many scholars approach efforts to confine Dakota people as guaranteed, “In Our Own Rightful Territory” instead focuses on the strategic movement of Dakota people across the US-Canadian borderlands to show how Dakota people strategically played the settler nations off one another. For the Dakota people who rebuilt their lives and communities across the border in Manitoba and Saskatchewan, they sustained an ongoing political relationship with the British and Canadian governments despite being characterized as “refugee” or “foreign” Indians. Additionally, these communities further participated in the social, political, and economic livelihood of the surrounding Indigenous and settler-colonial nations. While Dakota people now live on reserves in Canada, the period after the US-Dakota War lays a critical foundation for examining Dakota visibility and how they asserted rights to home, belonging, and the making of Dakota futures in Mni Sota Makoce
Theoretical Aspects of Electric Field Gradients in Relation to Nuclear Magnetic Resonance
Get PDFThe electric field gradient (EFG) is a physical quantity which reveals a wealth of infor- mation about the properties of materials. Arising from the local electronic environment in a material, its interaction with a quadrupolar nucleus results in energy level splitting, the transition frequencies of which can be measured by way of nuclear magnetic resonance (NMR). This dissertation is primarily concerned with the calculation of EFGs from first-principles for a variety of purposes, both theoretical and experimental. First, the NMR theory of spin 3/2 particles in a magnetic field is developed in a novel, exact, and analytical way using fictitious spin-1/2 formalism. From derived closed-form expressions of the spectrum, it is shown precisely how the EFG affects the spectrum for different materials. Next, the ability of density functional theory (DFT) to accurately predict EFGs, which has been a central question since the advent of DFT, is quantitatively evaluated. Calculations from different projector- augmented wave potentials are compared and contrasted to each other, and compared again to experimental values as well as to other all-electron calculations, in a first-of-its kind holistic study. We discuss the limits and bounds on how accurate the calculations can be compared to experiment. Next, we show how these calculations have led to the development of the first DFT-based EFG database, in collaboration with the JARVIS database developers at the National Institute of Standards and Technology. Statistics of the database and comparisons to experiment, which are largely favorable, are discussed. Finally, a case study of how the EFG can be used as a probe into both electric and magnetic effects in Fe-based superconductors is presented. This study includes DFT calculations of the EFG in Ba(Fe1–xCox)2As2 and how it is influenced by spin fluctuations of the Fe magnetic moments. An argument is presented which proposes the presence of anomalously low frequency spin fluctuations in the paramagnetic phase that can be detected on the NMR timescale. This is an indication of residual magnetism making its way into the paramagnetic phase. Finally, it is shown how the EFG from NMR can be a direct probe of these fluctuations and the potential implications into the theory of superconductivity for these materials is discussed
Reading into the Rise of China
Get PDFCollective and individual reactions to the rise of China vary across nation-states within East and Southeast Asia. While political scientists have investigated changes in China’s relative power from many distinct levels of analysis and theoretical perspectives, they have focused less on its impact on public sentiments. The complexity of public sentiment formation becomes more apparent when exploring different sentiment trends in Japan, Vietnam, the Philippines, and Malaysia. These distinct national publics espouse various levels of trepidation towards China, despite facing similar challenges and opportunities from the increasingly powerful People’s Republic of China (PRC). While I do not dispute the fact that there are many causal forces shaping public sentiments, I contend that national media sentiment framing China is a necessary force in understanding its formation and evolution. I perform multiple tests using national corpuses of online newspaper articles and public opinion polls to explore the relationship between media sentiments and public sentiments. Drawing from the unique insights of Social Identity Theory (SIT), Self-Categorization Theory (SCT), and Media Effects, I model the role of nationalism, the cohesion of the nation-state, and the relevance of history in the formation of public perceptions towards China. I find media sentiments to be reliable predictors of public sentiment towards China, both collectively and individually
How Local Education Policymakers Define the Teacher Turnover Problem: A Case Study
Get PDFTeacher turnover, or those teachers who either move between schools or leave the profession entirely, is a growing problem in today’s education system. Though education research is flush with studies about turnover’s causes and the success of certain policy initiatives, little attention has been paid to the perspectives of those policymakers often charged with trying to “do something” about it. The purpose of this study was to examine the political contexts from which education policies – specifically, teacher turnover policies – are being designed and implemented. Using a single instrumental case study design, sixteen local policymakers from seven North Carolina school districts, were interviewed about their perceptions of the teacher turnover problem. Rochefort and Cobb’s (1994) problem definition framework was adapted to create a coherent framework for the organization and analysis of participant responses. Overall, the findings show that participants have a nuanced and informed understanding of teacher turnover in their school districts. Moreover, interviews revealed that several state-level decisions surrounding licensure and charter schools were having a profound impact on smaller school districts’ ability to retain teachers. A discussion of policy and research implications includes the importance of qualitative information to better understand teacher turnover data.
The Grade the Music Died: A Survival Analysis of Student Persistence in School Music Electives from 6th to 12th Grade
Get PDFAccording to ample claims from music educators, persistence beyond a student’s initial enrollment in middle and high school music is a real problem in the U.S. (Kratus, 2007; Williams, 2007, 2011) and worldwide (Ng & Hartwig, 2011), making one-time enrollment metrics a misleading indicator of music’s popularity in schools. Additionally, various lines of evidence show that prolonged engagement with music is associated with positive developmental outcomes for adolescents (Elpus, 2013). My prior work (Tucker & Winsler, 2023) looking at persistence in music during the transition from 8th to 9th grade showed that only 1 in 4 students persist during the transition to high school, and high academic achievers and students with disabilities were less likely to drop out of music during this transition. While this work provided valuable insight into music persistence, exploring differences in rates and predictors of persistence over a much larger time scale is the next step in this line of research. The current dissertation built off prior work from the Miami School Readiness Project (MSRP; Alegrado, 2021; Alegrado & Winsler, 2020; Tucker & Winsler, 2023; Winsler et al., 2020) and prospectively followed an ethnically-diverse (62% Hispanic), low-income (78% in poverty) sample of adolescents from the beginning of middle school to the end of high school (6th–12th grade) to better understand persistence in school music electives (band, chorus, orchestra, guitar) across all of middle (n = 4,165 music students) and high school (n = 2,194 music students). Multiple discrete-time maximum-likelihood survival analysis models (Allison, 1982) were run to identify the proportion of students that dropped out of (“did not survive”) music each grade (e.g., 6th to 7th, 7th to 8th, etc.), and how particular factors (predictors of persistence; e.g., gender, ethnicity, poverty status, prior academic achievement, etc.) increased or decreased the probability of dropping out of music in each grade. Results confirm the concerns of many music educators, providing evidence of persistence problems throughout middle and high school with more students leaving music (as opposed to staying) at each grade transition. For students that began enrolling in music in 6th grade, 51% have dropped out of music by 7th grade, and 82% dropped out by 8th grade. As for students in high school (students in music in 9th grade, including late-joining music students that started enrolling in music after 6th grade), 57% of students drop out by 10th grade, 85% by 11th grade, and 95% drop out by 12th grade. High reading test scores and attending an arts-focused school were always related to reduced odds of dropping out of music in middle and high school, while gender, ethnicity, giftedness, and ELL status were never related to music dropout. Also, some predictors were important in some grades, but not others. High GPA was related to lower odds of dropout throughout middle school, and again in the last grade of high school, but GPA was unrelated to dropout in the first few grades of high school. Depth of family poverty was an indicator of increased odds of dropping out of music all the way through middle school but was unrelated to music dropout in high school. Students with disabilities were less likely to drop out of music their senior year, but disability status was not linked to dropout in any other grade. Moving to a new school was related to higher music dropout rates in every grade except for the final grade of high school. Additional survival analyses were run within each music subtype (band, chorus, orchestra, guitar), and results varied somewhat by music subtype. By better understanding which students and which grades present the biggest risk for no longer persisting in music in secondary school, scholars and educators alike will be able to utilize a more targeted approach to researching, and ultimately attempting to increase, student persistence in music across all of middle and high school
CRITICAL INQUIRY ON RACISM AND ANTI-RACISM IN US MEDICINE
Get PDFThe social uprising of 2020 and the disproportionate impact of COVID-19 motivated an inward examination of the legacy of racism in medicine. This legacy is apparent through the reification of race as a biological variable in the content of medical school curricula (despite countering scientific evidence); the documented adverse effects of race-adjusted diagnostic algorithms currently in use by clinicians; inequitable and exclusionary standards and learning climates along the medical pipeline; and the persistent dearth of Black physicians in the physician workforce relative to the general population, among other factors. Scholarly inquiry is needed to understand the systemic depth of racism in US medicine and to inform an anti-racist agenda. We conducted a three-part qualitative investigation to understand and center (1) Black women medical student perspectives on issues surrounding race, racism, and racial disparities in medical education; (2) Black women medical student experiences and perspectives on diversity, equity, and inclusion in medical school; and (3) the lived experience of Black primary care physicians across their trajectory from medical education to practice