Regents of the University of Michigan - Ann Arbor

NSF Awards · FY 2024 · 2024-09

As the challenges facing society grow more complex, there is increasing recognition that engineers must consider the social and environmental contexts in which their designs will exist in order to create effective products, systems, and processes that improve global quality of life. However, engineering curricula often focuses on technical design performance, and provides little training on how to contend with environmental and social challenges, leaving students ill-equipped to address sustainability during design. In support of the goals of the Research in the Formation of Engineers program and the NSF-Lemelson Initiative on Environmental and Social Sustainability in Engineering Education, this project will advance understanding of how to support engineering students’ preparation to address global social and environmental sustainability challenges. Specifically, this project will advance an educational approach focusing on priming that is adaptable across engineering disciplines and provide guidance for implementing this approach to emphasize social and environmental sustainability within existing curricula. Emphasizing sustainability in engineering may particularly resonate with and attract individuals from diverse and minoritized backgrounds drawn to impact-driven careers. Therefore, this project can contribute to creating a more inclusive and representative engineering workforce ready to address socio-technical challenges. This project seeks to develop, implement, and assess priming as an educational strategy to promote sustainable engineering design decision-making at the University of Michigan and the University of Arizona. Priming involves explicitly introducing a stimulus to students and assessing the subsequent response. Multiple prior studies have shown that, in controlled behavioral experiments, explicit sustainability language in problem statements results in better consideration of sustainability in subsequent design decisions. Additionally, supporting students to handle socio-technical complexity has been hypothesized to promote students’ sense of engineering agency beliefs and self efficacy. In this project, the team will adopt a mixed methods approach to investigate (1) the potential to scale up priming for sustainability as an engineering education intervention, (2) the role of priming on sustainable engineering design, (3) the impact of priming for sustainability on engineering students’ sense of agency and self-efficacy. The project team will first develop a range of sustainability primes, informed by literature on engineering education, design processes, sustainability competencies, and the Lemelson Initiative’s Engineering for One Planet Framework. The team will work with engineering instructors to tailor sustainability primes to fit within existing engineering design courses. The team will then collect and analyze qualitative and quantitative data from engineering instructors and students. Initial interviews will be conducted with engineering instructors to understand their course and learning objectives and to identify opportunities to add in priming for sustainability. After the sustainability primes are implemented in courses, interviews will be conducted with students to garner detailed insights into their experiences in engineering design courses, the design artifacts resulting from their courses, and their perspectives on sustainability in engineering. Validated tools will be used to measure changes in students’ engineering agency beliefs and self-efficacy before and after exposure to sustainability primes within engineering design courses. The expected contributions of this project are multifaceted. First, this project will provide guidance for integrating sustainability into engineering design curricula, resulting in more sustainable design decisions by students. By creating adaptable priming interventions, the project will provide a scalable tool for use by a broad set of engineering institutions and disciplines to emphasize sustainability. Additionally, this project will enhance an understanding of the relationship between students' beliefs about their engineering capabilities and their consideration of sustainability, an area that remains underexplored yet has potential to broaden participation and retention in engineering education. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Marginalized communities disproportionately experience the effects of environmental degradation such as sinking infrastructure, urban flooding, and coastal land loss as a result of legacies of segregation and lack of access to resources. To support youth in Black and Afro-Indigenous communities in Southeast Louisiana, the research team will work collaboratively with local community organizations to develop and enact a justice-centered framework for water literacy that responds to children’s experiences and concerns about the environmental water issues that impact their everyday lives. The project will contribute to knowledge of how community-engaged science curriculum and teaching projects build relationships between communities and schools and how students and teachers grapple with the justice dimensions of issues that have disciplinary and social implications. In partnership with a network of public charter schools in New Orleans, Louisiana, the research team will engage in four years of design-based research that centers community knowledge and lived experience. Guided by a steering committee of local water-focused community leaders and organizations, the team will work with approximately 16 teachers and 640 students in grades 3–8 to develop and study the implementation of the justice-centered water literacy curriculum units. Additional products will include professional development tools designed to amplify the community’s experiential and historical knowledge as central to science learning. This collaborative project is funded by the EDU Racial Equity in STEM Education activity, which is supported by the Directorate for STEM Education (EDU). This activity supports research and practice projects that investigate how considerations of racial equity factor into the improvement of science, technology, engineering, and mathematics (STEM) education and workforce. Programs across EDU contribute funds to the Racial Equity activity in recognition of the alignment of its projects with the collective research and development thrusts of the four divisions of the directorate. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

NON-TECHNICAL SUMMARY Research in quantum materials has led to the discovery of many novel materials with exotic physical properties, which are essential for future technologies. A special group of material known as iridium oxides has attracted much attention because they promise to help us understand unusual quantum states. Extreme conditions such as high pressure could reveal unexpected quantum states that are useful for advanced technologies. This project, supported by the Solid State and Materials Chemistry program in the Division of Materials Research at NSF, aims to systematically explore new quantum states in iridium oxides under high pressure. It also provides thorough training for all participating students, as well as visiting students and professors through the visiting scholar program, focusing on advanced experimental and computational techniques for creating and studying a wide range of materials in the principal investigators' laboratories. TECHNICAL SUMMARY Quantum phenomena driven by strong spin-orbit coupling are among the most important topics in modern materials chemistry and physics communities. This project aims to elucidate the complex relationship between crystal structure, chemical bonding, and strong spin-orbit coupling in iridium oxides, synthesized under high pressure and high temperature. Experimentally, the research will focus on exploring Ruddlesden-Popper structural motifs, Srn+1IrnO3n+1 (n= 1, 2, and infinity) to understand exotic magnetism, Mott Insulators, electronic behaviors, and potential for superconductivity. Chemical doping will be systematically applied to adjust electron counts and elicit a variety of quantum states. Concurrently, theoretical simulations, utilizing Dynamic Mean Field Theory (DMFT), will offer vital insights into the intricate interactions that facilitate the emergence of exotic quantum states in iridates. The project will enable transformative research in using high pressure and high temperature to assist quantum materials discovery and study. The outreach and educational initiatives will enhance broader impacts by fostering the development of the next generation of scientists in quantum materials and high-pressure techniques. This includes the establishment of annual workshops and visiting scholar programs, with a priority for women and underrepresented minority students, to cultivate a diverse community of experts in this cutting-edge field. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

There are more than 50,000 islands in the world, accounting for 17% of the total land area and inhabited by 10% of the global population. The US accounts for 18,617 islands, where the cost of electricity such as in Alaskan and Pacific islands can be 4-8 times higher than the average in the US. The same is true for remote coastal communities, such as 200 miles of Outer Banks of North Carolina, 120 miles of Florida Keys, and many islands in the Great Lakes. For power utilities, these communities rely on imported fossil fuels or miles of umbilical cables, which are vulnerable to earthquakes, wildfires, hurricanes and storms. While the electricity supply is one of the challenges limiting socio-economic development of remote island and coastal communities, vast energy resources are available from ocean waves along the 95,471 miles of US coastline. The power density of ocean wave energy is over 10 times that of solar power and 5 times as much as wind power. Attempts to harvest this resource date back to 1799, when the first patent was issued. To date, about 250 concepts of wave energy converters (WECs) have been proposed, but none of these have achieved commercial success. There is not even a widely-accepted criterion by which to judge which WEC concept is most favorable. The objective of this project is to drive and achieve research convergence of ocean wave energy conversion for empowering remote coastal communities through transdisciplinary research across engineering, economics, environmental, and sociological dimensions. The team expects to achieve convergence for powering remote communities within 4-5 years. In the longer term, wave energy can directly benefit a large proportion of the U.S. population without long-distance transmission, since over 53% of the U.S. population is concentrated within 50 miles of the shoreline. The project will provide significant potential to improve the economic development of under-served coastal communities by identifying a practical route to renewable electricity, thereby increasing their resilience to natural disasters, and empowering the local economy. It will also substantially benefit education from K-12 to graduate students in four universities with an emphasis on professional skills development. This project will drive convergence of ocean wave energy research through community-engaged decision making, 3D techno-economic socio-environmental assessment, and transdisciplinary co-design methodology. The goal will be achieved in two phases. Phase I will develop the WEC convergence roadmap, screen and down-select 2-3 lead WEC design concepts. This will be achieved by creating 3D assessment metrics to systematically evaluate technological feasibility, economic viability, and socioenvironmental acceptability in the early foundational concept and design stage. Phase II will investigate the leading design concepts through transdisciplinary co-design and optimization, and validate the convergence through community engagement and ocean tests. Inspired by the drug discovery process, the project will use a market-pull convergence procedure based on the needs of remote coastal communities to screen various WEC concepts from the beginning. This is in contrast to the prevailing approaches in wave energy research and development. The project includes a multidisciplinary team consisting of experts in engineering, environment, sustainability, social science and an external advisory board with community end users and OEM developers to implement a transdisciplinary, community-engaged approach to this research challenge. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project aims to understand how sleep and memory are intertwined in the brain by measuring the changes that occur in synaptic connections between neurons during sleep. Such changes are thought to be the fundamental processes underlying the solidification of memories in the intact brain. Incorporating long-duration recordings of neuronal activity at microsecond resolution, this research will leverage sophisticated recording and statistical tools to observe how synaptic connections evolve during sleep and memory tasks in order to uncover the exact mechanisms by which sleep plays a role in the consolidation of memories. Such insights are expected to address many central open questions in contemporary neuroscience regarding memory and the function of sleep. They could also lead to new ways of addressing memory disorders and developing therapeutic interventions for neuropsychiatric conditions in which sleep and memory are impacted. This project will help train undergraduate and master’s students from underrepresented populations and develop a course in Biological and Artificial Neural Networks, helping prepare students for careers in biomedical and computational sciences. The proposed study addresses a critical gap in our understanding of synaptic modifications during sleep and learning by leveraging advanced extracellular neurophysiological techniques and statistical tools. The statistical approach outlined for inferring microcircuit structure from spike trains is designed to be robust to nonstationary background dynamics, and is complemented by a detailed experimental strategy comprising key objectives. Utilizing bilateral recordings in hippocampal regions CA3 and CA1, this research will track spike trains at microsecond resolution from large neuronal populations during spatial memory tasks and various sleep stages. Fine-timescale analyses of these spike trains will infer and compare excitatory and inhibitory connectivity during pre- and post-task sleep, testing the Hebbian hypothesis that synaptic connections between co-active neuron pairs are strengthened following awake learning. Focusing on sleep following the task, these analyses will also identify dynamic changes in CA3/CA1 microcircuits over time, testing the hypothesis that connections engaged during learning are strengthened during sleep, while others undergo downregulation. The design identifies the effects of learning and sleep on microcircuit dynamics, and aims to capture the general principles of synaptic plasticity in a memory-critical brain region. The research will interrogate long-standing theories regarding the role of learning and sleep in modulating hippocampal microcircuit connectivity, potentially leading to significant advances in our understanding of neural plasticity and memory consolidation. This project is funded jointly by the Neural Systems Cluster of the Division of Integrative Organismal Systems in the Directorate for Biological Sciences and the Division of Information and Intelligent Systems in the Directorate for Computer and Information Science and Engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project develops novel causality-guided approaches for reliable threat detection and forecasting in complex event streams. Understanding causality is crucial because it allows us to identify the true drivers behind anomalies and pinpoint critical events that will significantly impact future event streams. For instance, to swiftly adapt to extreme climate shifts, it is essential to detect unusual earth movements or severe weather patterns that causally induce these shifts. Recognizing these causal relationships enables the implementation of preemptive countermeasures and enhances long-term forecasting. Similarly, in the context of information hazards, identifying latent patterns in social media posts that causally drive the spread of misinformation is vital. Understanding these causal drivers allows for quicker assessment and recognition of future threats, making it possible to take timely and effective action to ensure public safety. Moreover, the benefits of such methods extend far beyond security applications. They can unlock mechanistic insights into scientific event streams like neural activities, enriching the collection of techniques for scientific discovery. This project opens new lines of research, expanding the domain and scope of algorithmic threat detection. Specifically, it focuses on three key research topics: (1) causal inference for observed event streams with latent confounders and nonstationarity, (2) causal representation learning for latent event streams, and (3) causal anomaly detection and long-term forecasting. Leveraging the Hawkes process model—a self-exciting point process model—the investigators will establish a formal framework to determine when and how causal links can be inferred from partially observed and potentially non-stationary event sequences. The identified causal relationships will enable comprehensive situational awareness while pinpointing anomalies and providing long-term forecasts. The mathematical theory, algorithms, and software produced through this research will be transformational. This project aims to establish a foundational understanding of causality for algorithmic threat detection, provide principled algorithms for analyzing complex event streams, and broaden the application of these methods to diverse social and scientific domains. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Embodied intelligent networks are collections of distributed autonomous agents that can sense, reason, communicate, and act, leveraging suggested commands by human operators and/or external machine-learning algorithms. Scalable and reliable coordination among such agents can benefit society in tasks that range from environmental monitoring to transportation to national defense. But achieving scalability is challenging due to the agents' limited resources vs. their resource-demanding tasks that are often combinatorial and NP-hard. Achieving reliability is challenging due to (i) the agents' limited observability the environment, (ii) the environment's unpredictability, and (iii) the external commands' untrustworthiness, i.e., their lack of performance guarantees. This CAREER proposal will lay the theoretical and algorithmic foundation to overcome these challenges by introducing coordination and online-learning capabilities that enable multi-agent networks to (i) self-configure their communication topology to balance the trade-off of scalability vs. coordination performance, (ii) adapt online to unpredictable environments, and (iii) reap the benefits of external commands, managing the risks of erroneous commands. The proposed combinatorial optimization approach will be transformative by characterizing the trade-off between scalability and coordination performance via submodularity theory, and by contributing online-learning coordination algorithms that can balance the trade-off by tuning the degree of decentralized coordination among the agents, even in unpredictable and untrustworthy environments. The proposed research efforts will be evaluated in information gathering tasks via both physics-based simulations and field experiments. The research outcomes will provide practical methods for the distributed intelligence of critical infrastructure networks of the future such as multi-robot networks with humans in the loop, air-land-sea connected autonomous vehicles, and ubiquitously deployed sensors. Applications range from information gathering for environmental monitoring, disaster response, and surveillance to motion coordination and monitoring for traffic control in smart cities. The research efforts will also be integrated with educational efforts to enable a diverse future workforce that can design, deploy, and interact with embodied intelligent networks. Specifically, the planned educational efforts will engage students from the middle-school level up to the undergraduate level. The efforts will culminate in hands on research experiences with multi-quadrotor systems equipped with the proposed decision-making and decentralized-communication capabilities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Although the proton has been studied for over 100 years, it still is not fully understood. Until about 15 years ago, there seemed to be agreement among various experiments for how large the proton is. All that came into question when an experiment using muons, the heavy cousins of the electrons, displayed a large, unexplained discrepancy in the size of the proton compared to using electrons. This discrepancy was entirely unexpected, as the proton's size should not depend on whether it is measured with electrons or muons. This became known as the proton radius puzzle. The main physics program supported by this award is an attempt at solving this 14-year old puzzle about the real size of the proton. This research program will train a postdoctoral fellow on cryogenic techniques and targets. The involvement of junior researchers in this effort is important to ensure that there will be sufficient expertise in the nuclear physics community and beyond to support the future need for cryogenic instrumentation. The junior researchers will also have the opportunity to get involved in hardware, simulation and analysis projects and learn valuable skills in several programming languages and in the analysis of large data sets. The studies of the Michigan group at PSI aim to reassess the proton charge radius and the discrepancies that remain by performing the first simultaneous measurement of elastic electron and muon scattering off the proton, which is afforded by a beam that contains positively and negatively charged electrons, muons and pions. This approach has never been attempted before by another research collaboration and carries high promise to resolve the proton radius puzzle. Due to their specific expertise in building and running cryogenic targets, the Michigan group will lead the unpolarized target effort at MUSE and support the polarized target effort at Fermilab. This program builds on the expertise the group has gained and is a natural extension of the group's work over the past years. It provides a balanced mix of hardware, simulation and analysis projects, which will benefit the postdoc, and it will allow the U-M group to play a key role in the MUSE experiment at PSI. Education and training of postdoctoral fellows, as well as outreach aimed at the general public is an important aspect of this research program, particularly its international component, as it will expose them to physicists from many different countries, fostering cultural exchange and giving them the opportunity to develop their communication and leadership skills. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This research project will lead to a fundamental understanding of how bacterial proteins adapt and change in response to chemicals and antibacterial compounds introduced by humans. Antiseptic handsoaps and cleaning agents are commonly used to control bacteria that cause disease. Bacteria possess proteins to resist these antiseptics. The goal of this project is to understand how these antiseptic resistance proteins work. In addition, this research will address how antiseptic resistance proteins change over time when bacteria are exposed to antiseptics. This project will support the laboratory training of a postdoctoral scholar and undergraduate students. An additional goal of this project is to develop a museum exhibit at the University of Michigan Natural History Museum. Visitors to the museum exhibit will learn about how antiseptic resistance spreads among bacteria. This museum exhibit will inform members of the public about the project’s research findings. This project addresses the molecular evolution of the Small Multidrug Resistance (SMR) family of membrane proteins, which efflux quaternary ammonium antiseptics. Integral membrane proteins experience a vastly different set of physical parameters than soluble proteins, and thus the evolutionary pressures acting on membrane proteins are also very different. Current understanding of how membrane proteins evolve increasing structural and mechanistic complexity, and how they evolve new transport functions, is limited. This research addresses these questions by applying a combination of phylogenetic, biophysical, and x-ray crystallographic approaches. Specifically, this project will analyze the biophysical basis for quaternary ammonium antiseptic export by SMR proteins (objective 1), the historical evolutionary events that lead to quaternary ammonium and polyamine export (objective 2). These lines of research are broadly relevant to ongoing evolution of bacteria in response to quaternary ammonium antiseptics, to which SMR proteins provide resistance. In objective 3, the investigators will translate the research findings regarding the interplay of SMR proteins bacterial antiseptic resistance to an audience of the general public using a museum exhibit at the University of Michigan Museum of Natural History. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The broader impact of this Broadening Participation for Engineering Track 2 (BPE- Track-2) project will be to enhance knowledge about how to increase the number of women in higher-power (tenure-track) engineering faculty and leadership positions. Though many stakeholders prioritize increasing gender equity for academic faculty, statistics show that women are over-represented in lower-power faculty positions (non-tenure track). These lower-power faculty roles are often not eligible for higher career advancement, including campus leadership positions. Without gender equity in higher positions of power, the benefits of a diverse workforce cannot be fully realized. We are researching why and how women are positioned in lower- or higher-powered faculty roles in academia. To do this, we will learn from people along this career path, including women graduate engineering students, women in lower-power engineering faculty positions, and women engineering faculty in higher-power positions. By interviewing these people and studying their experiences, we will be able to more deeply understand the underlying mechanisms that result in these power imbalances for women, including women of color. This understanding will then inform changes that institutions can make to support women faculty advancing toward leadership positions in academia. The proposed project leverages a qualitative approach to answer the unexplored research question: How can institutions support the advancement of women faculty in non-tenure track (NTT) ranks? Our study will explore women graduate student and faculty experiences through the lenses of intra-occupational gender segregation and social cognitive career theory to identify key mechanisms that influence women’s career decisions in academia and the factors that support women’s transitions from NTT to tenure-track (TT) roles. The project will leverage our prior research to determine: 1) how trainee perceptions of TT and NTT roles develop and influence career decisions; 2) how NTT women faculty experience their roles and seek career advancement; and 3) what are the pathways, including barriers and supports, of advancement of women from NTT to TT ranks. We will interview 40-50 participants, including (1) women engineering graduate students, (2) women NTT faculty in engineering, and (3) women TT faculty in engineering. Interview collection will include semi-structured, quantitative comparative, and critical incident techniques and analysis will include thematic analysis and corresponding quantitative comparative, and critical incident analysis. We will leverage our results to inform research-based practices to support career development and institutional policies that support gender equity. This project was partially supported by the NSF ADVANCE program which is designed to foster STEM faculty equity by identifying and eliminating organizational barriers to the full participation and advancement of diverse faculty in academic institutions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The description of nature at its most fundamental level should describe all matter and phenomena in the physical universe with a set of basic pieces – elementary particles – and an explanation of the forces between them. In the current state of the art, called “The Standard Model,” the normal matter that surrounds us is made up of electrons, protons and neutrons bound together in atoms and their nuclei, and the neutrons and protons are made up of elementary constituents called quarks. The Standard Model does not, however, describe everything that has been observed and does not provide an explanation of how the universe evolved with more matter than anti-matter; additional particles and forces must exist. The muon, like the electron, is an elementary particle and is produced as the earth is bombarded by cosmic rays from space and at accelerators. Measuring the magnetic and electric properties of muons, neutrons, and atoms with great precision is one of the most promising ways to explore the “new physics” of additional particles and interactions. This research requires developing technologies for controlling and detecting magnetic fields that also have potentially broad applications to medicine, geological exploration, and defense. This research focuses on contributing to the answers to these fundamental questions, developing widely useful magnetic technologies, and providing exceptional training for a cohort of undergraduates, graduate students, and post-docs with broad skills, who will lead the way to solving crucial technical and intellectual problems. The investigations will take part at the national facilities Los Alamos National Lab, Argonne National Lab, and Fermilab, advancing the capabilities of these technical facilities and enhancing training opportunities. Precise measurement of the magnetic and electric properties of fundamental particles and atoms provides information that may inform the extensions to the Standard Model of elementary particle interactions, often called Beyond Standard Model or BSM physics. This research will continue collaboration on the Fermilab Muon g-2 experiment with the primary activity of leading the analysis of the space and time dependent measurement of the muon-averaged magnetic field that connects the muon spin precession frequency to the muon magnetic moment anomaly and the Standard Model. Calibration of the magnetic field measurement chain using the Mark-II absolute 3He magnetometer with precision below 10 ppb (parts-per-billion) will be completed. The electric dipole moment of the neutron (nEDM) will be measured using the world's leading ultra-cold neutron source at Los Alamos National Lab with focus on magnetic field measurement and control including continuing new developments of optical magnetometers, in part through commercial collaborations. The electric dipole moment of 129Xe will be measured with more than 10-times improvement over the current precision using the Los Alamos nEDM magnetics systems. Throughout, this research will advance novel approaches to monitoring magnetic fields using arrays of magnetometers that apply to both the Fermilab and Los Alamos experiments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Part 1 Under what conditions do states surveil and censor their citizens? How are the two tactics related to each other and other forms of repression and control? To what extent have states concealed their use of these tactics? States have increasingly wielded surveillance and censorship, both digital and physical, as tools of political influence at home and abroad. Yet, there exist scant theoretical and empirical advances to help understand these phenomena. Consequently, scholars know little of how and when states employ these levers and how their use has evolved with technological advancements. To address this critical knowledge gap, the investigators produce, analyze, and disseminate a novel dataset, the Global Surveillance and Censorship Scores (GSCS) database. The project utilizes mixed methods to collate quantitative and qualitative historical and contemporary data, including a diverse set of existing human rights reports. The resulting dataset allows academics, practitioners, and policymakers to advance the study of human rights and repression. The project has key implications for American national security and policy, ranging from finance and healthcare to human and drug trafficking, which have been affected by surveillance and censorship practices. Part 2 Surveillance and censorship are key levers of power to control information. States have increasingly wielded them, digitally and physically, to compete for political influence at home and abroad. Yet, scant theoretical and empirical advances exist to help understand the phenomena. Consequently, we know little of how and when actors employ these levers, and how their use as repressive techniques evolve with technological advancements in the 21st century. The investigators use mixed-methods to collect quantitative and qualitative historical and contemporary data to develop the Global Surveillance and Censorship Scores (GSCS) database. Information is extracted on surveillance and censorship from a diverse set of existing human rights reports and other documents. Given the clandestine nature of surveillance and censorship, a latent variable models developed to address missing information and to assess the sensitivity of the model estimates to understand the extent to which states conceal the use of such tools. This Bayesian latent variable model is able to predict cases of missing information and aggregate information into country-year estimates. To further address bias in the reports, the investigators also conduct case studies using expert information, interviews, and archival research to validate the data. The project will allow researchers to generate new theories and empirical evidence to advance the study of human rights, censorship, and surveillance. The data and analytic deliverables will serve as a public good for the community of academics, practitioners, and policymakers. Surveillance and censorship increasingly shape geopolitics by controlling and manipulating information; understanding the evolution of censorship and surveillance can thus contribute to the development of sound foreign and security policies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Post-oil economies are increasingly demanded in the name of planetary sustainability and of economic diversification. Envisioning and constructing a future beyond oil has thus become a central preoccupation for policymakers, environmentalists, and researchers around the world. This dissertation project investigates the processes through which a post-oil economy is tangibly constructed and traces the varied effects of that endeavor on social and religious life. In addition to aiding a graduate student’s training in scientific research methods and analysis, findings from this project will be disseminated through environmental change conferences, think tanks, and popular journalistic outlets. Through eighteen months of ethnographic and archival research, the project engages state functionaries and independent entrepreneurs to examine the role of new tourism markets in the pursuit of a post-oil economic future. Specifically, the researcher investigates the institutional reforms and policy innovations through which religious tourism is transformed into a substantial sector of the economy. Already valued at $12 billion annually, the sector provides an opportunity to study a critical economic growth sector. The research simultaneously traces the effects of these reforms on the governance of religious tourism and on doctrinal conceptions of normative ritual practice. Methods include interviews, participant observation within these organizations, and a thematic analysis of archival materials and ministerial documents. In so doing, this doctoral dissertation project contributes to scholarly investigations of state economic transitions, state governance, and the confluence of religion and the economy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The Earth’s magnetopause is an electric current layer separating the magnetospheric and shocked solar wind plasmas and their magnetic topologies, often detectable by an abrupt change in local plasma and magnetic field conditions. Understanding the transferred energy and where and under which local and global conditions the most significant energy transfer occurs is important for predicting magnetospheric disturbances. Local processes at the boundary, coupled with the magnetospheric dynamics, the transferred energy powering space weather impacts in space and on the ground. For the first time, this project will extensively use in-situ observations to determine the statistics of the direct energy transfer through the magnetopause and construct an assessment of the importance of the boundary motion, which results in magnetospheric energy acquisitions and forfeitures. The work includes an inclusive research experience component for undergraduate students, which will contribute to educating the next generation scientists. A large statistical set of over 4,000 magnetopause crossings of the Magnetospheric Multiscale mission is employed to resolve the local energy exchange at the low-latitude dayside magnetopause. The conducted work analyzes multi-spacecraft electromagnetic field and plasma measurements to evaluate the magnetopause energetics, including the exchanged energy (entry vs. exit), its content (electromagnetic vs. hydrodynamic), and energy conversion rate at the boundary, as well as the dependence on the upstream solar wind conditions and magnetospheric state. The project will assess how the interplay between the current state of the system and the external driver reflects the outer boundary dynamics and provide the first spatial mapping of the energy transfer and its content at the low-latitude dayside magnetopause. The effects of the magnetopause motion due to varying solar wind flow and magnetospheric reconfigurations have yet to be accounted for in observational analyses. This project will evaluate the contributions of magnetospheric compressions and expansions to the system energy content and how the energy exchange processes are modulated due to the boundary motion. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project supports research focused on understanding population mobility subject to repeated flooding in regions that are historically unprepared to cope with such events. Repeated, low-attention flood disasters do not receive widespread media coverage compared to larger, catastrophic ones. Low-attention flood events are currently understudied, but their cumulative impacts are likely to compound underlying causes of risk, inequality, and poverty. Furthermore, there is not a good understanding of how they contribute to people’s decisions to evacuate, return, or permanently move. By filling the knowledge gap, this study aims to better inform local and regional policymakers responsible for designing policies for mitigation strategies and aid distribution before, during, and after these events. Considering the lack of data and the variety in mobility patterns from low-attention flood events, this research project leverages multiple data sources at multiple scales. Mobile phone data provides insights into broader mobility patterns that would otherwise be difficult to assess due to the smaller scale of these events. However, it is often biased towards certain demographics and, importantly, cannot provide reasons behind such mobility patterns. Therefore, mobile phone data is used to guide surveys and interviews to uncover experiences and causes for displaced populations, especially those missing from mobile phone data. These datasets are ultimately integrated to develop a holistic understanding of mobility due to low-attention flooding. Through this project, the research team not only introduces new methods to combine multiple sources of data but also advances understanding of population mobility from low-attention flooding to inform disaster planning and management. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project aims to build a mechanism for academia, industry, and the public sector to collaborate and co-design research and development (R&D) directions to simultaneously improve data systems and artificial intelligence (AI) systems. Such co-designed systems will be able to better address scientific and societal challenges, while avoiding the harm from the inappropriate use of data and AI, especially the harm on marginalized communities. The advancement of AI brings forward unprecedented promises for breakthroughs in science and for vastly improved policy-making. But at the current moment, the fast pace of AI development actually poses major challenges to scientists in academia and to public-sector organizations. One can use scientists in academia as the example. The advancement of AI technology far outpaces the scientists’ individual efforts to adopt AI. Many scientists are also not equipped with sufficient technical skills to adopt AI. As they rush to implement AI in research, many research outcomes have already become questionable and will harm the rigor, reproducibility, validity and trustworthiness of science. Similarly, any inappropriate use of AI in the government decision making process could result in serious harm. Meanwhile, AI resources and talents are overwhelmingly concentrated in industry, which is developing an increasingly larger number of powerful AI systems but they may not be aligned well with the needs of scientific research and government decision making. R&D direction co-design, which this project will explore, will help shape the development of emerging technologies, not just AI, so that they can impact science and society positively in more significant and faster ways. It will also strengthen the mentality of placing the needs of scientific research and public interest at the center of future technology development. In addition, this project will help foster a balanced and vibrant national research and innovation ecosystem, with academia, industry, government and community playing their unique and central roles. Such an ecosystem can effectively leverage emerging technologies and fuel future technologies. This project will bring together data science and AI methodologists from the University of Michigan and Microsoft, University of Michigan scientists who apply such data science and AI methods across research fields, and the city of Detroit data team. The scientific focus is to develop coordinated research on databases and new AI systems. This is because many AI systems are not yet optimal to deal with specialized data in scientific research and with government data. Conversely, much of the enormous amount of scientific data and government data are not constructed to leverage the new AI systems. Making data “AI ready” will be a continued priority as novel forms of AI continue to emerge that use diverse types of data representation and preparation. Coordinated database research and AI research will enable data and AI to be more compatible. Through workshops, presentations and technical demos, structured discussions and deliberations, the project participants will identify: 1) The traditional mechanisms of R&D direction design in industry and academia and their inefficiencies; 2) The next waves of AI systems and how they can advance scientific research and government decision-making; 3) Gaps in database research and AI research that can be filled through research co-design; 4) Possible harms to people and society, especially to marginalized communities, in the implementation of the new AI systems, and ways to mitigate the harms; 5) mechanisms to understand different priorities, perspectives and needs of different organizations and communities and ways to collaborate despite such differences; and 6) a concrete R&D direction based on the above considerations. The project team will employ social science theory and practice to enable equitable participation and deliberation. The project team will disseminate their work and recommendations to enable the scaling of such effort. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The White House's Ocean Policy Committee developed the Ocean Climate Action Plan in March 2023, prioritizing using the ocean’s power to mitigate climate change, including ocean waves and offshore wind energy. To take advantage of the leading research and facilities in European countries and better train the next generation of the workforce in the fields of offshore wind energy and ocean wave energy in the United States, this project annually selects a cohort of eight U.S. undergraduate and graduate students to engage in immersive research experiences at leading European institutions known for their advancements in ocean renewable energy. Through this international collaboration, students gain valuable skills, knowledge and connections, preparing them to become future leaders in sustainable energy technologies. In addition, this project also emphasizes diversity and inclusion, involving students from varied backgrounds and underrepresented groups, thus contributing to a more diverse and globally competitive STEM workforce. The project resonates across educational, economic, environmental, and societal domains, promoting diversity and inclusion within STEM fields, advancing technical knowledge in renewable energy, and preparing a new generation of scientists and engineers with global perspectives on sustainability challenges and opportunities. The research focuses on innovative solutions for ocean renewable energy, addressing critical areas such as control of wave energy converters, optimization of offshore wind platforms, offshore wind turbine reliability analysis, and mooring systems for marine energy devices. Students are sent to renowned European institutions including Maynooth University in Ireland, the University of Plymouth in the U.K., the Norwegian University of Science and Technology in Norway, and the Technical University of Denmark in Denmark. In this project, students work alongside renowned European experts, engaging in projects that involve advanced yet important topics such as control algorithm design, system optimization, reliability analysis, and structural analysis. By integrating academic research and cross-cultural experiences, this project aims to push the boundaries of current renewable energy technologies, stimulate creativity, and contribute to the global transition towards sustainable energy systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Recently there has been an explosion in the use of artificial intelligence (AI) techniques within astronomy. Astronomy is not immune to human and systemic biases, which go beyond representative datasets and agnostic machine learning algorithms. As emphasized in Special 1270 from the National Institutes of Standards and Technology, researchers should operationalize Trustworthy and Responsible AI and create new norms on how AI is built. This team of investigators will define these norms by identifying, characterizing, and mitigating gold standard labeling bias in galaxy shape classifications. These biases can cause downstream effects in (semi) supervised AI models. The goal of this project is to solve gold label bias mitigation by linking the effort to an interesting astronomical scientific use case. As an additional assessment, they will apply their techniques to medical imaging data to improve AI-assisted tumor detection. The researchers will train an AI system to predict the spatio-spectral properties of the stellar light inside galaxies from imaging data alone. This system will map resolved stellar properties like stellar mass, age, or metallicity to galaxy internal shape properties like bars, spiral arms, and central bulges. They aim to achieve an order of magnitude increase in the sample sizes of resolved stellar properties used for galaxy evolution studies. Other researchers can use this model to infer pixel-level properties that fall well below the typical signal-to-noise thresholds required for expensive spectroscopic studies. A critical component of this research program will be the identification, quantification, and mitigation of gold standard label bias, which they have shown to affect current human-based morphology datasets. In addition to the astronomical data, the team will utilize the screening mammography breast cancer detection dataset from the recent classification KAGGLE competition sponsored by the Radiological Society of North America. The PI will collaborate with staff and researchers in the Michigan Institute for Data and AI in Society (MIDAS) to identify additional datasets that can be studied to assess and mitigate labeling bias. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The demand for powerful and energy-efficient artificial intelligence (AI) is growing rapidly. Current AI hardware, which uses silicon chips, struggles to meet these needs for advanced AI models. This Emerging Frontiers in Research and Integration (EFRI) project will develop innovative computing systems inspired by the structure and function of the human brain. Specifically, the project will create advanced human brain organoids (hBOs). These are miniature 3D models of the human brain grown from stem cells in a lab dish. They contain various types of brain cells that organize themselves into structures resembling parts of the developing human brain. hBOs can process information and perform computations in ways that parallel the human brain's capabilities. This EFRI research will integrate multiple hBOs with different arrangements and connections to develop new computing architectures that are highly efficient in terms of energy consumption and computing power. In addition, Bioethicists will collaborate closely with engineering researchers at each step of the project to study ethical considerations related to public acceptance and oversight of hBO computing. This EFRI BEGIN OI project will develop an hBO-based biocomputing system that integrates neuromorphic computing theory, bioengineered hBOs, and critical bioethical research. It will advance theoretical concepts in biocomputing with human cortical neural networks by designing optimal neural networks and implementing adaptive learning mechanisms. The research will explore how factors like excitatory-inhibitory balanced networks, connectivity density, and network scale affect the computational capacity of hBOs. Additionally, the project will develop bioengineered multi-hBO systems with organized hBOs containing excitatory and inhibitory neuron populations in local microcircuits. These novel hBOs will interface with electronics to achieve real-time read-in and read-out of neuronal activity, leveraging the adaptive learning properties inherent in hBOs. This effort represents a critical step toward developing neuromorphic computing hardware capable of achieving superior computing power with low energy consumption. Importantly, the EFRI research will also address bioethical challenges associated with hBO-based biocomputing by refining an innovative approach to engineering ethics. It will ensure alignment with evolving standards in AI and biomedical research ethics, engaging policymakers and ethical committees to navigate the complex landscape of human biomaterial use in computing applications and fostering public trust and acceptance. Educational efforts within the EFRI project will reach diverse student populations, including K-12 and underrepresented groups, nurturing interest in STEM and biological research. Outreach activities will engage students in both the US and Israel with STEM challenges and offer interdisciplinary training opportunities for graduate students in both countries. This project is jointly funded by the Emerging Frontiers in Research and Innovation Program (BEGIN OI), the Directorate for Computer and Information Science and Engineering, and the Directorate for Mathematical and Physical Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This IRES project addresses the significant socio-environmental changes affecting dryland systems in Kenya, including arid, semiarid, and dry sub-humid areas, through the formation of a student-scout partnership to understand and promote sustainable and fair transitions in these socio-environmental systems. Selected undergraduate students undergo extensive preparation, including learning Swahili and studying dryland system sustainability and research methods. Each cohort of U.S. undergraduates spend eight weeks in Kenya conducting field research, using various methods such as GPS-tracking livestock, plant surveys, wildlife censuses, household surveys, and interviews. This research contributes to important findings in dryland sustainability while training a diverse group of future STEM professionals. This project investigates the sustainability of dryland systems by focusing on the essential role of mobility in connecting social and environmental components. It aims to understand pastoralists’ livelihood strategies and resource access and examines how to balance agricultural intensification with mobile herding. Methods include tracking livestock movements and assessing rangeland vegetation dynamics, which provide insights into rangeland governance that support dryland system resilience. The project is interdisciplinary, aligning with NSF’s goals to encourage convergence research and leverage data to understand system transitions and tipping points. Collaboration involves Cornell, Michigan, and Princeton, with mentorship and local support from long-term collaborators in Kenya. This project advances the scientific understanding of dryland sustainability and contributes significantly to training a new generation of U.S. researchers capable of addressing global sustainability challenges. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Many agricultural, farming, and industrial processes release excess nitrate into the environment, making it the most pervasive groundwater pollutant in the world. This poses a serious threat to human and ecosystem health. Capturing and converting low nitrate concentrations from groundwater and surface waters is exceptionally challenging. To address this pressing need for nitrate management across food and water systems, this project will bring together experts from various complementary disciplines to develop an integrated nitrate capture and conversion device that is efficient, low-cost, and powered by renewable resources. The device will use light energy to concentrate nitrate from waste streams (photocapacitive concentration) and electrically-driven chemical reactions (electrocatalytic conversion) to produce nitrogen and valuable chemicals such as ammonia. This approach will provide insights into the chemical, physical, and catalytic processes involved in nitrate concentration and conversion, as well as the socioeconomic factors that limit the adoption of nitrogen management technologies. The project outcomes will advance the design of sustainable resource recovery systems to manage the nitrogen cycle and may reduce the cost of nitrate treatment. Further, this research will empower resource-limited communities and industrial point source treatment operators to better address their nitrate water treatment needs. Graduate and undergraduate students at the University of Michigan, the University of Iowa, and the University of Texas at Austin will receive interdisciplinary technical training. The planned outreach activities will also provide opportunities to broaden the participation of underserved groups in STEM. This project aims to develop an integrated photocapacitive concentration and electrocatalytic conversion technology for nitrate treatment. The project includes four research thrusts focused on developing and understanding this nitrate treatment technology. The first thrust advances the discovery and design of selective photocapacitive systems to capture and concentrate nitrate. In the second thrust, the team will develop and test electrocatalysts made from inexpensive and earth-abundant elements that are durable and thermodynamically and kinetically compatible for nitrate capture and conversion to ammonia or nitrogen. The third thrust involves physics-based modeling and testing of the transport processes needed to optimize the photocapacitive capture and electrocatalytic conversion system. The fourth thrust assesses process sustainability using technoeconomic and life cycle analyses to promote technology adoption by impacted communities. By integrating photocapacitive and electrocatalytic tools, this project will create a technology platform that sustainably captures and transforms nitrate, a regulated human health risk, into useful products. This convergent research advances knowledge by simultaneously considering nitrate concentration and conversion, unlike existing studies that separate these steps. The project’s outreach activities include (1) creating an exchange program for interdisciplinary summer undergraduate research experiences to prepare students from underrepresented groups for graduate research; (2) engaging water treatment professionals and communities in Iowa and Texas who are working to address nitrate pollution; and (3) integrating best practices from NSF Research Traineeship programs focused on innovations at the nexus of food-energy-water systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The objective of this Smart and Connected Communities (SCC) project is to support research on mitigating flooding risk, improving water quality, and restoring ecological habitats through coordinated dam releases across communities within a watershed. Flooding is the leading natural disaster causing fatalities and property damage in the United States, and the increasing frequency and intensity of storms exacerbate this problem. Additionally, rural and low-income communities are disproportionately affected, as they often reside in low-lying areas prone to flooding. This project addresses these challenges by researching creation and implementation of a digital watershed system – an interconnected landscape of sensors and data analysis tools to manage water flow effectively. It provides environmental benefits, reduces flooding risk, and fosters social capital by building trust and collaboration among diverse groups of community members. The broader significance lies in its potential to transform watershed management across the country, offering a scalable, technology-driven solution to pressing water and environmental issues. The primary goal of this research project is to develop and implement a digital water management system that enhances coordination among dam operators to optimize water flow and improve ecological outcomes. Three integrative research objectives are pursued: (1) Investigating the role of social capital in decision-making among rural and urban dam operators, and translating these insights into digital tools that promote coordination; (2) Developing new methodologies to understand the relationship between river flows and fish habitats, and setting flow targets based on real-time sensor data; (3) Creating novel control algorithms to regulate water flow using model-predictive control (MPC) theory, ensuring stability and efficiency even under varying levels of human operator participation. The interdisciplinary team, comprising dam operators, watershed planners, regulators, social scientists, ecohydrologists, and engineers, deploys a network of sensors and a web-based decision support system to facilitate real-time data sharing and predictive modeling. The output includes fundamental scientific insights and practical solutions for watershed management, potentially serving as a model for similar efforts nationwide. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Acoustic communication can bring individuals together, coordinate activities, and maintain or end associations. However, the precise role played by sound in mediating both physical and physiological responses of members of their fluid groups has not been uncovered. This is in large part due to 1) an inability to simultaneously monitor individual vocalizations, the resulting movement of both focal and conspecific animals during highly dynamic behavior, and the physiology of the animals; and 2) the lack of a physics-based model of how the animals perceive sound in their environment. To date, scientists have tended to investigate how individual-specific signature whistles are used for identification, how signature whistles are used as contact calls, how acoustic features may indicate stress levels and how one dolphin may copy the signature whistle of another to initiate an interaction. However, how the animals perceive acoustic information during coordinated movement is still an open question. Further, the connection between the resulting behavior and emotional state of the animal is not well understood. Uncovering how the perception of acoustic information drives complex collective behavior requires a new framework to collect, analyze, and synthesize data from multiple dolphins at the same time. This includes a new understanding of how animals select, organize, and interpret acoustic information in a system where multiple signals can occur simultaneously and in a complex acoustic environment. To this end, this award will combine experimental measurements of sound and movement with physics-based models of acoustic perception and animal swimming mechanics to generate new knowledge about how context drives observed group movement patterns. Leveraging this approach, the investigators will create first of their kind maps between observed animal movement/acoustics and emotional state using physiological measurements collected in conjunction with controlled behavioral experiments. This effort will generate new knowledge about how coordinated behavior is influenced by environmental and behavioral context, how the physics of the acoustic environment influences communication, and how acoustic information is used to coordinate collective behavior. Intellectual merit of the award stems from the Principal Investigator’s efforts to: (1) Use a physics-based model of acoustic perception to generate a new understanding of collective dolphin behavior; (2) Enable the fundamental scientific understanding of how behavior and features from vocal cues can be used to identify physiological and emotional state of the animal; (3) Create dynamic movement profiles from individual animals to provide new knowledge about individual and group biomechanics during collective behavior; and (4) Investigate how a specialized acoustic signal, a whistle with learned individually distinctive features, is used to facilitate behavioral interactions. New knowledge derived from the research will impact the areas of physics-based modeling, biologging, communication, animal behavior, animal welfare, conservation, and acoustics. This award will generate new knowledge about how vocal communication, with influence from emotive state, facilitates collective behavior in bottlenose dolphins. An understanding of how information encoded in vocal cues is used to coordinate behavior will improve our fundamental understanding of dolphins. The resulting ability to estimate emotional state non-invasively from acoustic parameters of calls and observed movement will impact animal welfare and conservation in managed and wild settings. The team of researchers will also have impact through a multi-tiered education and outreach program, with a special emphasis on recruiting talented individuals from a variety of non-dominant fields in STEM. K-12 education and public outreach opportunities in the greater Chicagoland area will leverage existing resources at Brookfield. This collaboration will create opportunities to engage and share new knowledge generated by the project about these important biological systems with the local community, and aid in the conservation and management of cetaceans in general. At the University of Michigan, this novel engineering project for the study of an engaging biological system will be used to recruit students from a diverse and underrepresented pool of students outside of the traditional track. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Astronomers are just beginning to understand when and how planets form around young stars, with deep implications on the prospects for life in the Universe. While rocky planets similar to Earth are located close to their stars, these innermost regions are typically too close-in to study with conventional telescopes. This project will combine light from multiple telescopes operating as an interferometer – the CHARA array - to measure the temperature and map the surface density of the inner disk surrounding solar-mass and intermediate-mass young stars. Repeated observations will track moving clumps of dust that could be indicating accretion/wind physics or local planet formation. Outreach programs at rural community colleges will draw local high school students into higher education. An inspiring educational experience is planned for middle-schoolers in “Wolverine Pathways,” a University of Michigan program offered to communities in the Detroit-metro area who are historically under-represented in state colleges. The CHARA Array is the longest-baseline optical/infrared interferometer in the world. Researchers at the University of Michigan developed the MIRC-X and MYSTIC instruments which combine all six CHARA telescopes with broad 1.1-2.5μm wavelength coverage simultaneously, while also supporting access by the broader astronomical community through open time administered by NOIRLAB. In commissioning data, the team has discovered hot, time-variable emission inside the expected dust destruction radius. In this project, they make a modest upgrade to the telescopic instrumentation; measure multiwavelength data to assess the disks temperature; expand the target sample to stars of diverse masses, luminosities, ages, and accretion rates; and measure time-domain follow-up data. This project improves research infrastructure by providing new software tools, such as the first MYSTIC-ABCD pipeline, written in Python and C, and it makes the source code publicly available. Regarding broader impact, an outreach program with St. Clair County Community College develops authentic research modules with an internet-enabled telescope, supporting STEM students transferring to 4-year colleges. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Why are some organisms more diverse than others, both in numbers and in their lifestyles? With more than 1,700 known species in rivers and lakes of the Americas, Africa, the Levant, Madagascar and India, cichlid fishes –one of the largest families of freshwater fishes– can help answer these questions. Although their evolutionary timescale is poorly understood, cichlids boast an extensive fossil record. These poorly-studied fossils could provide a window into the group’s ancient past. This project will study living and fossil cichlids to provide a better picture of when major events in cichlid evolution occurred. The project will also explore how cichlid ecology changed through time by comparing fossils with today’s living species, with the goal of understanding the life history of ancient cichlids. The project will support a postdoctoral researcher, two PhD students, a Master’s student, a technician, and undergraduate students, emphasizing development of transferable skills across STEM and non-STEM fields. The researchers will engage public audiences through university and public museums in the US, and in collaborating museums in Kenya, Brazil and the Dominican Republic. Museum-based activities and associated materials will be produced in English, Portuguese, and Spanish and shared with all participant institutions. Undergraduate teaching modules will be developed and made available as online resources for educators. Cichlid fishes represent a textbook model system for studying adaptive radiation, sexual selection, speciation, and the interplay between ecology and evolution. Despite their importance in biological research, our understanding of cichlid evolution is limited by the lack of an accurate timescale for the group’s evolutionary history. While fossils represent the principal source of temporal data in macroevolutionary studies, a barrier their incorporation is a lack of phenotypic character sets that include both extant and fossil species. Additionally, the surprisingly rich cichlid fossil record, a direct source of temporal information, remains incompletely integrated with the growing body of data available for living species. This work will produce phylogenomic data along with the first comprehensive morphological character set for cichlids, and new phenotypic data extracted from well-preserved fossil specimens. The project will: (i) leverage computed tomographic (CT) examination of modern and fossil specimens to create a morphological framework for explicitly including fossil cichlids in a phylogenetic context with living species; (ii) combine these phenotypic data for extinct and living cichlids with existing phylogenomic resources to infer a comprehensive, dated genus-level phylogeny for cichlids; and (iii) test the impact of fossils on inferred patterns of cichlid ecomorphology and macroevolution on timescales of tens of millions of years. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.