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Deep Learning Approaches for Chaotic Dynamics and High-Resolution Weather Simulations in the US Midwest
Get PDFWeather prediction is indispensable across various sectors, from agriculture to disaster forecasting, deeply influencing daily life and work. Recent advancement of AI foundation models for weather and climate predictions makes it possible to perform a large number of predictions in reasonable time to support timesensitive policy- and decision-making. However, the uncertainty quantification, validation, and attribution of these models have not been well explored, and the lack of knowledge can eventually hinder the improvement of their prediction accuracy and precision. Our project is embarking on a two-fold approach leveraging deep learning techniques (LSTM and Transformer) architectures. Firstly, we model the Lorenz 63 and 96 systems, crucial for grasping chaotic dynamics. By harnessing these neural networks on local computers and the RCAC GPU cluster (Gilbreth), we aim for accurate multi-step forecasts, emphasizing hyperparameter influence on model performance. This research sets a foundation for advanced, transformer-based weather predictions. Secondly, noting the dearth of high-resolution weather data in the US Midwest, including cities like Chicago, we\u27re employing Nvidia\u27s FourCastNet model. Integrated with vision transformers and Adaptive Fourier Neural Operators (AFNOs), it simulates severe Midwest weather events. Using the RCAC\u27s Gilbreth cluster and tapping into the ECMWF Reanalysis (ERA5) dataset, FourCastNet forecasts up to a week ahead in under two seconds, outpacing existing systems. This efficient model promises enhanced weather predictions and extreme event risk assessments. Our goal: simulate the potent January 23, 2016, mid-Atlantic snowstorm and contrast results with traditional forecast models
Beyond Whiteness: Revisiting Jews in Ethnic America
Get PDFThe concept of ethnicity, once in vogue, has largely gone out of fashion among twenty-first-century social scientists, now replaced by models of assimilation defined in terms of the construction of whiteness and white supremacy. Beyond Whiteness: Revisiting Jews in Ethnic America explores the benefits of reconfiguring the ethnic concept as a tool to analyze the experiences of twentieth-century American Jews—not only in relation to other “white” groups of European descent, but also African Americans and Asian Americans, among others. The essays presented here, ranging from comparative studies of Jews and Asians as “model minorities” to the examination of postethnic “Jews of color,” demonstrate that expanding ethnicity beyond the traditional Eurocentric frame can yield fresh insights into the character of Jewish life in the modern United States.https://docs.lib.purdue.edu/casden/1014/thumbnail.jp
Essays on Market Segmentation and Retailers\u27 Competing Strategies
No full textThis dissertation focuses on exploring U.S. food retailers’ strategic interactions and the impacts on consumers. Specifically, I examine food retailers’ strategies on segmenting consumers, conducting price discrimination, and designing their product portfolio in the context of the U.S. yogurt market. The first essay examines the segmentation strategies employed by food retailers, with a focus on the use of advanced machine learning techniques (i.e., K-means clustering) to group consumers based on various characteristics, including demographics and purchase history. The second essay applies the data-driven market segmentation obtained in the first essay to a second-degree price discrimination model. The third essay relaxes the implicit assumption made in the first two essays that consumers’ choice set is fixed, and studies a non-price strategy, namely, adjusting assortment, that is adopted by food retailers in response to regulations. By analyzing the retailers’ strategies on market segmentation and responses to regulations, this dissertation aims to shed light on the strategic interactions of food retailers and consumers, and the competitive landscape of food market in general.Understanding the strategies employed by food retailers is of utmost importance in agricultural and food economics as it directly influences consumers and their purchasing decisions. The food retail industry in the U.S. is highly competitive, with retailers continuously devising tactics to attract and retain customers. Dimensions of competition such as pricing strategies, product assortment, promotional activities, and customer service can significantly impact consumers’ choices and behaviors. Investigating the strategies employed by food retailers not only provides insights into their business operations but also sheds light on how these strategies affect consumers.The first essay explores the application of machine learning methods in consumer segmentation under different information environments. Machine learning methods become popular in economic and marketing research, partly because of their flexibility in application. Although recent studies apply these advanced methods to various topics including water, housing, health, and food markets, much is less known about using machine learning methods to facilitate firms’ market segmentation decisions. Using Nielsen Consumer Panel data, I show that K-means clustering, one of the unsupervised learning methods, can be applied to conduct market segmentation. From the retailers’ perspective, incorporating more consumer information (i.e., purchase history) leads to the change in segments consumers belong to.The second essay assesses the effectiveness of data-driven market segmentation in enhancing price discrimination models. Price discrimination models are commonly adopted by firms to optimize revenue and profitability by customizing prices to different customer segments. Existing studies often rely on exogenous assumptions for consumer segmentation, which may or may not be applicable in practice. This study advances the existing literature by replacing the consumer segment assumption with data-driven market segmentation obtained through K-means clustering. The results are then applied to the second-degree price discrimination model to analyze how sensitive the firms optimal profits are under different consumer information environments. The findings reveal that adding consumer information to consumer segment leads to a more inelastic demand for the consumer segments and an increase in firm’s profits
Effectively Disenfranchised? Framing and the Youth Climate Movement in the United States
No full textA worldwide movement has emerged in recent years, bringing millions of young people together to demand action on climate change. While youths’ high level of vulnerability to climate change could make them especially credible, and therefore powerful, messengers on this topic, there has been relatively little scholarly attention on youthactivism and the nuances of framing by youth climate activists in particular. This gap may be especially important in the United States, which represents a substantial portion of global emissions but has historically struggled to establish enduring climate policy. Can this new generation of activists – many of whom are not yet old enough to vote – uniquely impact climate policy in the United States? My dissertation uses a multimethod approach to explore this question, focusing on communication by youth activists. I begin by examining the distinct frames that U.S. youth activists use to describe the issue of climate change, and exploring how they perceive those messages will influence the policymaking process. I do this using interview data with youth activists and examining Tweets, finding that youth activists often rely on climate science frames rather than justice-related frames that arguably “fit” well with their identities and vulnerabilities as youth. Next, I consider the effect of different climate frames on three sets of actors relevant to policymaking on this issue: (i) the general (adult) public, (ii) the youth public, and (iii) policymakers. More specifically, I draw on data from an original survey experiment and interviews with local- and state-level officials. I find clear evidence that the “fit” between message framing and messenger source matters – youth can be effective messengers about climate change, but particularly when they invoke arguments about the intergenerational and environmental injustices of climate inaction. The role of source identity is a critical contribution to the political communication and climate framing literature. Although many scholars have pointed to source identity as an important factor, the relationship between message content and source identity has been underexamined in the literature regarding climate change to date. This study also contributes to the framing literature through a focus on age as an important facet of source identity and by examining the causal influence of justice-based frames. Finally, this study aims to contribute to the social movement literature by a focus on the unique impacts of communication by youth climate activists. Given youths’ high level of vulnerability to climate impacts, this dissertation work could have notable environmental justice implications as well
Harmonic Resurgence: Reclaiming the Godino Twins’ Journey Through Hip Hop
No full textHarmonic Resurgence: Reclaiming the Godino Twins\u27 Journey through Hip Hopis a groundbreaking dissertation that combines Hip Hop music and critical fabulation to amplify the story of the Godino twins, conjoined Filipino musicians who led an all-Filipino jazz band in the United States from 1929 to 1936. This interdisciplinary project challenges the systematic erasure of marginalized histories from archives, confront historical omissions, and celebrate the invaluable contributions of Filipino Americans to American music. By exploring themes of race, cultural exchange, disability, and the transformative power of music in shaping identity and society, the dissertation engages in critical conversations and strives for justice, equity, and inclusivity in the cultural landscape.The dissertation consists of a Hip Hop concept mixtape and a comprehensive literary component. The mixtape creatively expresses the Godino twins\u27 journey and magnifies their significance, while the literary component provides a theoretical foundation and explores relevant fields such as Asian American and Filipino Racialization, Filipino Americans performing Black Music, and Disability Studies and Performance. These chapters intertwine academic inquiry with artistic expression, challenging dominant narratives and fostering a more inclusive understanding of American music history.Through the fusion of Hip Hop music and critical fabulation, the project disrupts the prevailing narrative of erasure and creates a space that recognizes and celebrates marginalized stories. It addresses the historical omission of the Godino twins and highlights the broader erasure of Filipino American history. By acknowledging the resilience and talent of Filipino musicians, the dissertation contributes to decolonization efforts and promote a more comprehensive representation of diverse narratives within American music history.Drawing on the enduring nature of the blues tradition and the interplay between Filipino and African-American musical traditions, the dissertation explores connections between the Godino twins\u27 story and contemporary musical forms. It emphasizes responsible engagement and collaboration while honoring the contributions and struggles of African-descended communities. The project envisions a future where marginalized voices are amplified, cultural contributions are deeply appreciated, and a more inclusive cultural environment is fostered.In conclusion, Harmonic Resurgence: Reclaiming the Godino Twins\u27 Journey through Hip Hop offers a transformative exploration of the Godino twins\u27 story, challenging erasure, celebrating Filipino contributions, and contributing to decolonization, justice, and equity. By combining Hip Hop music and critical fabulation, this dissertation presents a powerful narrative that disrupts traditional historical narratives, amplifies marginalized voices, and envisions a more inclusive representation of American music history
Coupling Nanomechanical and Chemical Characterization for Evaluating Properties of Smallscale Molecular Crystals
No full textMolecular crystals are used in a wide variety of applications, from pharmaceuticals and sweeteners to energetic materials. Understanding their chemical and mechanical properties provides insight into their performance and use. These properties are especially critical for energetic material systems, which may be sensitive to impact and require specific handling and storage practices. The mechanical properties of energetic molecular crystals are typically determined using nanoindentation by measuring elastic modulus, hardness, yield point, and fracture behavior. Reports of the properties and mechanical behavior of as-grown molecular crystals are limited due to the relative difficulty of performing good quality measurements. This work’s contributions include the first known measurements of elastic and plastic properties for crystals of DAAF, CL-20, NTO, ETN, and R-salt.When studying molecular crystalline systems, some important assumptions and behaviors typical to metallic and ionic systems begin to break down. The energetic material diaminoazoxyfurazan (DAAF) exhibits highly irregular mechanical behavior, which is likely explained by a complex combination of chemical and material attributes. This work investigates and compares the irregular mechanical response in DAAF—including high variance in mechanical properties, broad range of load-depth behavior, and non-conforming indentation impression geometries—to other energetic molecular crystals. The yield points (i.e., onset of plasticity) for several energetic materials, whose elastic modulus values range from 9.6 to 25.5 GPa, are also compared to identify the parameters that govern the onset of plasticity. This includes an investigation into yield point dependence on (or independence from) elastic modulus, hardness, near-neighbor spacing, and activation volume. When these materials reach the onset of plasticity, the maximum shear stress in each material ranges from 2-7% of their elastic modulus value. Analysis of the yield behavior in these materials suggests that there is not a strong correlation between yield stress and hardness, thus establishing that the mechanisms governing dislocation nucleation are not controlled by hardness, and vice-versa. By recognizing and accounting for the added complexities associated with inherently non-spherical molecules in a crystal lattice, this work advances the comprehension of mechanical response in molecular crystal systems
Laboratories of Government: Private Foundations in Modern American Political History
No full textThroughout the twentieth-century private foundations played a central––but often overlooked––role in the policy-making process. Born in debates over the first income tax, Congress initially rejected the creation of tax-exempt institutions funded by a single individual. State legislatures proved less hesitant and created an incongruent system of defining and regulating private foundations. After the postwar economic boom, the number of foundations had grown to such a point that in 1961 even the IRS could not say how many foundations existed nor make definitive statements on their activities. A decade of investigation revealed that foundations were among the nation’s largest shareholders of publicly traded companies raising new questions as to the influence of foundations over the economy and corporate leaders\u27 use of foundations to avoid taxation. In 1969, a diverse coalition of legislators, regulators, and foundation leaders worked to pass the Tax Reform Act of 1969, which forced foundations to be more transparent about their expenditures and holdings, set limits on family involvement on foundation boards, and limited the amount of shares foundations could hold of a single company. This new tax policy led to the professionalization of private foundations as a sector as the new regulations required foundations to act more like their for-profit counterparts in organization, transparency, and accountability.And yet, foundation-produced reports, oral histories, and material from presidential and congressional archives all reveal how these measures inadvertently increased the influence of foundations on public policy. By showing compliance with the new regulations, historically wealthy white business leaders gained an outsized role in shaping the boundaries of policy debates as presidential administrations increasingly relied on private foundations to supply public goods. Lawmakers depended on policy briefs and studies funded by foundation grants as they crafted legislation, congressional offices and presidential administrations filled their staffs with foundation employees, and foundation leaders entered the public fray as pundits in the 24-hour news cycle. This project explores the widespread influence of private foundations throughout contentious policy debates over energy, education, and health care that dominated the last third of the twentieth century and reveals how foundations became key institutions channeling capital and individual goals into the implementation of state power and reshaped the policymaking process
Metaprogramming Program Analyzers
No full textStatic program analyzers are vital tools to produce useful insights about programs without executing these programs. These insights can be used to improve the quality of programs, e.g., detecting defects in programs, or optimizing programs to use fewer resources. However, building static program analyzers that are simultaneously sound, performant, and flexible is notoriously challenging.This dissertation aims to address this challenge by exploring the potential of applying correct-by-construction metaprogramming techniques to build static program analyzers. Metaprogramming techniques manipulate and transform programs as data objects. In this thesis, we consider static program analyzers as the objects to be manipulated or transformed. We show that metaprogramming techniques can improve our understanding, the construction, flexibility, and performance of program analyzers.We first study the inter-derivation of abstract interpreters. Using off-the-shelf program transformation techniques such as refunctionalization, we demonstrate that big-step abstract interpreters can be mechanically derived from their small-step counterparts, thus building a functional correspondence between two different styles of abstract interpretation.To build high-performance program analyzers, we exploit the first Futamura projection to build compilers for abstract interpretation and symbolic execution. The first Futamura projection states that specializing an interpreter with respect to an input program is a process equivalent to compilation, thus providing a practical way to repurpose interpreters for compilation and code generation. We systematically apply this idea to build programanalysis compilers by writing analyzers as staged interpreters using higher-level abstractions. The staged interpreter can be used for generating sound and performant analysis code given a specific input program. Moreover, the approach enables using abstractions without regret: by using higher-level program abstractions, the analyzer can be written in a way that is close to its high-level specification (e.g. big-step operational semantics), and by compilation, the analyzer is performant since it does not need to pay the runtime overhead of using these abstraction mechanisms.We also develop novel type systems that track sharing and separation in higher-order imperative languages. Such type systems are useful both for general-purpose programming languages and for optimization of domain-specific metaprograms such as those programanalysis compilers
Essays on Government Policy and Food Safety
No full textFood safety is of high importance to prevent foodborne illnesses that can negatively affect public health and the economy. Preventative measures can be taken by government agencies, food-related workers, and consumers to reduce the occurrence of such illnesses. This paper examines the impact of government policies on food safety from the perspective of consumers, restaurant employees and employers, and food processing workers. Each essay provides novel insight into how food safety practices interact with policies.The first essay explores how food safety recalls affect consumer behavior. Using household-level scanner data, the study investigates if consumers adjust their meat purchases following a government meat recall notification. Results show that although there is a statistically significant decrease in consumer meat purchases after a meat recall, it is short-lived and has a small economic impact. The study also finds that consumer recall response varies depending on household demographic and recall characteristics. These findings reveal the effectiveness of government food safety policies in raising consumer awareness and consumer responses to food safety recalls.The second essay studies the impact of minimum wage policies on service quality in the restaurant industry. A wage increase can simultaneously affect employee productivity through increased earnings and employer management practices through increased labor costs. The study measures whether a wage increase affects the customer service quality and food safety provided by low-wage employees and if there are any spillover effects of a wage increase on service quality offered by employers. The study uses restaurant-level food safety inspections and jurisdictionlevel minimum wage changes in the US between 2010 and 2019. Results show that a wage increase improves service quality and reduces overall restaurant violations, mainly driven by a decrease in employee-associated violations. However, the study also finds an increase in severe employerassociated violations that can have adverse effects on consumer health outcomes. These findings reveal the mixed effects of unintended government policies on restaurant food safety.The third essay investigates the effect of minimum wage policies on product food safety in the meat and poultry processing industry. The study uses high-frequency plant-level meat, poultry, and egg product inspection (MPI) data and local minimum wage announcements (i.e., ordinances) and implementations between 2012 and 2019. Results show that a wage increase improves food safety practices at meat and poultry processing plants, as measured by improved MPI compliance rates. The study shows that improved compliance rates are likely due to enhanced worker performance through increased wages. The study suggests that an increase in the minimum wage improves worker earnings and performance, which leads to improved MPI compliance rates. The study also finds that improved compliance rates occur mostly within the five months following the minimum wage increase implementation, indicating that workers display present-looking behavior rather than forward-looking behavior in terms of worker performance. These findings highlight how wage increase policies can improve food safety practices in the food processing industry
Shock-Wave / Boundary-Layer Interaction in Flow over the High-Speed Army Reference Vehicle
No full textHypersonic flow over two generic missile configurations was investigated using CFD methods. CFD results were compared with experimental results obtained by the hypersonic flight lab at Texas A&M University. Baseline RANS computations involving the missile configurations at a zero deg angle-of-attack were performed, along with computations at higher angles-of-attack. As the angle-of-attack was increased, complex vortex interactions were observed in the region between the fins. Increasing the angle-of-attack generally increased heating on the windward side of the missile geometries, especially on wall surface regions adjacent to the fin-root vortices. The results presented highlight observed fin region vortices and regions of intense heating on the body surface. DES simulations methods were also used to explore unsteady aspects of flow around the two generic missile configurations through time-accurate CFD simulations. Power spectral plots were generated to quantify the dominant frequencies of large-scale unsteadiness