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Conditioning Elections: The Instability with Dynamic Voters
No full textThe stability of electoral outcomes is a cornerstone of democratic legitimacy, yet real-world elections increasingly exhibit volatility driven by dynamic voter populations and shifting preferences. By treating elections as a function f(x) where x represents voter choice, we can study the conditioning of election outcome functions under perturbations, analogous to sensitivity analysis of numerical solvers. This paper investigates the mechanisms underlying instability in elections when voters and their beliefs evolve over time, focusing on the effects of conditioning decisions on anticipated future changes. By surveying classical and contemporary models of voting rules under dynamic settings, this paper demonstrates how seemingly stable aggregation mechanisms can lose robustness in the face of preference fluctuations, and analyze the strategic implications when voters or election designers incorporate information about forthcoming population changes into their choices. Through mathematical analysis and illustrative simulations, it is revealed that conditioning on future voter dynamics introduces new avenues for equilibrium selection, strategic manipulation, and unpredictability. Using data from current and historical datasets from the American National Election Survey, along with the most recent Cooperative Election Study dataset, we find that factors such as quality of campaigns and perceived fairness of elections are major factors in stabilizing or destabilizing elections. These findings highlight critical vulnerabilities and design principles for election systems in dynamic societies, offering both theoretical insights and practical considerations for sustaining stability in democratic processes
Paseando por el museo: El diálogo entre las pinturas / Strolling Through the Museum: A Dialogue Between Paintings
No full textPALABRAS PRELIMINARES (ESPAÑOL)
Paseando por el museo: El diálogo entre las pinturas es el segundo volumen de la antología de la clase Español 344-Spanish Writing Workshop. El primer volumen se titula A través de las fronteras: Un estudio de arte comparativo, y salió en el primavera de 2023. En este curso (primavera de 2025), los estudiantes interactuaron con y analizaron varias formas del arte—incluyendo la poesía, los cuentos, los ensayos, las películas, y las pinturas—con el objetivo de mejorar sus habilidades de escribir en español y sus destrezas con el análisis. Para este proyecto, los estudiantes no solo observaron las obras de arte, sino que también aprendieron sobre los trasfondos históricos, sociales, y políticos que forman cada obra.
En esta tarea para el curso, los estudiantes fueron asignados el nombre de un pintor de una variedad de países hispanoparlantes. Después de hacer una investigación preliminar sobre su artista, la clase hizo una excursión al Museo de Arte de California Hilbert en Chapman.
Al tener en cuenta a su artista asignado, los estudiantes tuvieron que encontrar una pintura en el Hilbert con similitudes con la obra de su artista hispano, ya sea en estilo, contenido visual o representación. Luego, tenían que componer un ensayo comparando las dos obras de arte a base de un tema en particular seleccionado por ellos. Esta antología incluye cinco excelentes ensayos de estudiantes de la clase, todos los cuales establecen conexiones y reconocen interesantes paralelismos entre sus obras de arte. Estos estudiantes han bosquejado un diálogo colorido que destaca algunas de las obras más interesantes del mundo hispano en colaboración con el arte de California.
PALABRAS PRELIMINARES (ENGLISH)
Strolling Through the Museum: A Dialogue Between Paintings is the second volume of the SPAN 344 Spanish Writing Workshop essay anthology. The first volume, Across Borders: A Comparative Art Study, was published in Spring 2023. In this course (Spring 2025), students interacted with and analyzed various forms of art—including poetry, short stories, essays, movies, and paintings—with the goal of improving their Spanish writing abilities and analytical skills. For this project, students not only observed physical art pieces; they also learned about the historical, social, and political landscapes that shaped each work.
In this assignment for the course, students were randomly assigned an artist from a variety of Spanish-speaking countries. After doing some preliminary research on their artist, the class took a field trip to Chapman’s Hilbert Museum of California Art.
Keeping their assigned artist in mind, the students had to find a painting in the Hilbert with similarities to the work of their Hispanic artist, whether in style, visual content, or representation. Later, they had to compose an essay comparing the two pieces of art on the basis of a particular theme they selected. This anthology includes five excellent essays from students in the class, all of whom draw connections and recognize interesting parallels between their artworks. These students have sketched a colorful dialogue that highlights some of the most interesting works of art from the Hispanic world in collaboration with the art of California
Sounds of Hidden Agents: The Development of Causal Reasoning About Musical Sounds
No full textListening to music activates representations of movement and social agents. Why? We test whether causal reasoning plays a role, and find that from childhood, people can intuitively reason about how musical sounds were generated, inferring the events and agents that caused the sounds. In Experiment 1 (N = 120, pre-registered), 6-year-old children and adults inferred the presence of an unobserved animate agent from hearing musical sounds, by integrating information from the sounds’ timing with knowledge of the visual context. Thus, children inferred that an agent was present when the sounds would require self-propelled movement to produce, given the current visual context (e.g., unevenly-timed notes, from evenly-spaced xylophone bars). Consistent with Bayesian causal inference, this reasoning was flexible, allowing people to make inferences not only about unobserved agents, but also the structure of the visual environment in which sounds were produced (in Experiment 2, N = 114). Across experiments, we found evidence of developmental change: Younger children ages 4–5 years failed to integrate auditory and visual information, focusing solely on auditory features (Experiment 1) and failing to connect sounds to visual contexts that produced them (Experiment 2). Our findings support a developmental account in which before age 6, children\u27s reasoning about the causes of musical sounds is limited by failure to integrate information from multiple modalities when engaging in causal reasoning. By age 6, children and adults integrate auditory information with other knowledge to reason about how musical sounds were generated, and thereby link musical sounds with the agents, contexts, and events that caused them
BOARD # 271: NSF IUSE 2315777: Training Engineering Students to Be Better Learners: A Course-Integrated Approach
No full textLearning is a lifelong process exercised within and beyond the classroom, and a vital skill in almost all technical professions. Engineers, in particular, are impacted by rapidly evolving technologies and practices that require continuous learning and adaptation long after their training and the initial transition into their professional careers. However, despite the critical role of learning in their academic success and profession, engineering students experience academically rigorous and challenging courses with minimal emphasis or conscious focus on learning strategies that power effective learning. Often-used learning strategies such as rereading, highlighting, repetition, and memorization are intuitive for many students, yet do not facilitate the higher-order thinking required to solve difficult engineering problems and understand concepts. As a result, weak learning strategies are an important factor in why students often initially struggle in their courses to reach the level of concept mastery and the ability to synthesize, apply, and evaluate problems using engineering principles; and why they may continue to struggle as lifelong learners. The consequences of ineffective learning are already transcending in students’ academic careers: slowing their curricular progress and affecting their ability to adjust to university life, build self-regulatory skills, and gain a sense of control over their learning experiences. These challenges stem from the fact that the engineering curriculum has traditionally emphasized teaching content and material while assuming that students can manage their own learning. Integrating self-regulated learning skills into the engineering curriculum holds great potential to promote students’ learning skills and growth mindset. The aim of this NSF IUSE-funded project is to develop, implement, and evaluate course-integrated self-regulated learning skills training interventions. One challenge of such interventions is to have a thorough understanding of how engineering students are learning, and what learning strategies and learning behaviors they most engage with, so we can develop a targeted intervention to promote engagement of effective learning strategies/ behaviors and move away from ineffective learning strategies and behaviors. Although there is a range of literature that developed surveys and empirical studies to understand various components of students’ self-regulated learning skills, such as motivation, learning strategies inventory, metacognition, and growth mindset, there is no single survey and study that covers all these aspects. In addition, the majority of the empirical studies about learning strategies\u27 utility were conducted in psychology, math, physics, and biology classes, with limited data on engineering students. Thus, as the first step of our project, we developed a complete set of survey questions to understand all three dimensions of students’ self-regulated learning (growth mindset, cognitive strategies, metacognition), with some questions adapted from existing validated surveys, and some newly developed questions. Using the convenience sampling method, in a pilot study, the surveys were sent to 831 engineering students in five mechanical and electrical engineering courses, which were taught by the four instructors who are NSF project team members. In this paper, we demonstrate the survey results with a general descriptive analysis for the general students\u27 sample, as well as for various demographics groups, such as gender, first-generation college students, transfer students, and other underrepresented groups
Novel Lipid Polymer Design for Nucleic Acids Delivery
No full textRNA interference (RNAi) is a powerful tool that can selectively downregulate the expression of any protein without the need for expensive and time-consuming drug development processes. Despite the initial excitement and extensive efforts, the potential impact of RNAi in clinical settings has been limited due to challenges in delivering RNA molecules effectively and safely. In parallel, the CRISPR/Cas9 system has revolutionized genome editing by enabling targeted, permanent genetic modifications; however, its success also depends on the development of reliable delivery systems for single-guide RNA (sgRNA)-Cas9 complexes. Lipid nanoparticles (LNPs) have emerged as one of the most successful non-viral carriers for nucleic acids, highlighted by the approval of the first small interfering RNA (siRNA) therapy and the rapid deployment of LNP-based mRNA vaccines against COVID-19. However, achieving efficient and targeted delivery of nucleic acids to solid tumors remains a significant barrier. Polyethyleneimine (PEI), in particular, was once considered the gold standard in polymer-based nucleic acid delivery due to its high transfection efficiency, but its clinical application has been limited by toxicity. In this study, we investigate a novel lipid–polymer nanoparticle (LPNP) platform for the targeted delivery of sgRNA- Cas9 complexes to triple-negative breast cancer (TNBC) cells (MDA-MB-231) and siRNA against Respiratory Syncytial Virus (RSV) viral proteins in human lung cancer A549 cells. We hypothesize that incorporating hydrophobically modified polyethyleneimines (PEIs) into optimized LNP formulations will enhance the delivery of nucleic acids. We first optimized LNP formulations as a benchmark for cellular uptake, cytotoxicity, and silencing efficiency, guided by advanced experimental designs using Design-Expert software. We then systematically replaced the ionizable lipid with specifically engineered cationic polymers, either partially or fully, to generate hybrid LPNPs. Our findings demonstrate that these LPNPs significantly improve nucleic acid delivery to MDA-MB-231 cells. To further confirm the platform’s effectiveness, we tested the best siRNA formulations in A549 cells. Overall, LPNPs showed strong cellular internalization, which translated to silencing efficiency, suggesting that the LPNP systems could be useful in breast cancer and beyond
Between Hard and Soft Power: A Historical Analysis of U.S. Defense Diplomacy
No full textIn recent years, countries around the world—those of Europe but also Japan, China, and Russia—have accelerated their efforts to use military assets as instruments of diplomacy. This trend has contributed to the rising prevalence of the term “defense diplomacy” in national security discourse. The United States is no exception. Its abundant military assets and its global network of bases clearly demonstrate that it is the world’s leading practitioner of defense diplomacy. Yet the United States lacks a clear strategic document outlining the concept. Moreover, because existing definitions remain theoretically ambiguous and methods for assessing the effectiveness of defense diplomacy initiatives are underdeveloped, the topic has received limited attention from both academic and policy communities. In other words, the defense diplomacy debate rests upon an unstable conceptual foundation.
This study deconstructs the components of defense diplomacy drawn from existing scholarship and argues that its essence lies in the realm of soft power policy. Put simply, defense diplomacy refers to the use of military assets—primarily by defense institutions during peacetime —to generate soft power effects. Focusing on its soft-power dimension, this study seeks to establish a comprehensive understanding and analytical framework for defense diplomacy by proposing a new definition that clarifies its objectives, instruments, and actors.
Furthermore, this thesis traces the evolution of U.S. defense diplomacy along the broader trajectory of American foreign policy. This historical investigation reveals that, as the United States expanded its territory and ambitions, its military forces were increasingly tasked with roles that extended beyond their traditional missions. U.S. defense diplomacy emerged in earnest after World War II and reached its golden age during the Cold War. The overlap between the expansion of American ambition and the rise of defense diplomacy is no coincidence. Historical analysis shows that the soft-power effects of defense diplomacy at times served to conceal America’s ambition for global military primacy, thereby helping to legitimize its position as a superpower.
Long before Joseph Nye introduced the concept of “soft power” in 1990, the United States had already been attempting to transform its military assets into instruments of attraction. It appears to have achieved tangible results in such cases as the postwar occupation of Japan, the Cold War, and the war on terror in the Philippines. In the context of a new Cold War with China, defense diplomacy should be regarded as a policy instrument deserving of attention—just as soft power was in the 1990s
Strategic Interactions and Gender Cues: Evidence from Social Preference Games
No full textThis paper studies trust, reciprocity, and bargaining using a large-scale online experiment in six Latin American countries. Participants were randomly assigned to play trust and ultimatum games under conditions in which the gender of their counterpart was either disclosed or withheld. On average, gender disclosure did not affect behavior. However, disaggregated results show systematic differences. Men displayed higher levels of trust and reciprocity, particularly when interacting with women, and offered larger shares to women in bargaining. Women, by contrast, reciprocated more when paired with men. These findings show how gendered interactions can influence economic behavior, even when counterpart information is conveyed minimally
A Silver Spoon Effect Reduces Lifetime Fitness in a Declining Loon Population
No full textA complete understanding of factors that influence animal fitness requires that we measure not only those occurring day to day in the life of an animal but also those that operate on longer time scales. Here, we investigated silver spoon effects (fitness impacts resulting from conditions faced early in life) and carryover effects (fitness impacts caused by environmental factors in a previous season) in a northern Wisconsin population of the common loon (Gavia immer). The mass of a loon chick divided by its age, an indication of food it received from its parents in its first 4 to 6 weeks of life (“chick condition”), affected both the likelihood of survival to adulthood and, among territory settlers, the number of chicks it fledged as an adult. Only one carryover effect was evident: increased ocean pH on the wintering ground had a modest positive effect on territory settlement rate. However, cohorts of loons that faced unfavorable ocean conditions in their first year yielded adults that fledged many chicks, which suggests that selection resulting from poor ocean conditions removed weaker phenotypes. The robust silver spoon effect in this species helps us understand a current and alarming pattern in the Wisconsin loon population: the sharp decline in the survival of chicks to breeding age
Bridging Machine Learning and Islamic Scholarship: A Study in Hadith Translation and Similarity Analysis
No full textTranslation of Islamic religious texts poses unique challenges requiring both linguistic and theological expertise. This study explores the application of neural machine translation (NMT) models to Arabic-English hadith translation while analyzing semantic similarity patterns across different human translations. Using the complete Sahih Bukhari corpus (7,550 hadiths) as the primary dataset, we adopt a dual approach combining transfer learning and comprehensive neural network analysis to demonstrate the critical impact of corpus size on model performance.First, we fine-tune a pre-trained MarianMT Arabic-English translation model on the full Sahih Bukhari corpus, comparing models trained on 40 hadiths versus 7,550 hadiths. Performance is evaluated using BLEU scores, demonstrating that corpus scale significantly affects translation accuracy: the 40-hadith model achieves a BLEU score of 9.90, while the 7,550-hadith model shows substantial improvement, illustrating how adequate training data is essential for specialized domain adaptation. Second, we implement and compare ten distinct Siamese neural network architectures to analyze semantic similarity between multiple English translations of the same hadith. These architectures range from simple LSTMs to advanced models incorporating attention mechanisms, bidirectional processing, and transformer encoders. Comprehensive evaluation addresses the severe overfitting observed with limited data: expanding from 40 to 7,550 hadiths improves validation accuracy from 42% to over 70%, reducing the training-validation gap from 56 to under 15 percentage points. An ensemble model combining the top three architectures achieves optimal performance. Our analysis integrates computational metrics with theological accuracy assessment, leveraging expertise in Islamic studies to evaluate model performance. Findings indicate that while NMT models achieve reasonable quality for straightforward passages, they struggle to preserve religious nuance and precise Arabic terminology. Results provide quantitative evidence that adequate corpus size is the critical factor for meaningful model generalization. This research contributes to computational religious studies and underscores the irreplaceable role of human expertise in translating sacred texts, with implications for Islamic education and digital humanities scholarship
A Certainty-Weighted, Belief-Based Model of Political Attitudes: A Bayesian Analysis of American Public Attitudes Toward the Affordable Care Act
No full textThis study proposes a novel, certainty-weighted account of the process by which political beliefs shape political attitudes. Building upon expectancy-value frameworks, this paper introduces belief certainty as a moderator of belief impact. A Bayesian partial-pooling approach is used to test a model positing how beliefs about what the Patient Protection and Affordable Care Act does and does not do relate to overall attitudes toward the law. This analytic method manages the complexity of multiple potentially correlated beliefs and evaluations by imposing a structural constraint to avoid multicollinearity and enable accurate estimation of parameters. Data from a nationally representative sample survey of American adults support the model\u27s core propositions. Counterfactual simulations further reveal that belief certainty substantially amplifies the weight of both accurate and inaccurate beliefs, thereby intensifying attitudes and amplifying polarization. These findings highlight the role of belief certainty in shaping political judgments and offer a methodological pathway for researchers to model the interplay of multiple correlated political beliefs in an era of abundant—sometimes erroneous—information