Colorado State University

NSF Awards · FY 2025 · 2025-01

The project will support the goals of a) advancing the field of STEM education through helping to identify factors that support or hinder the persistence of undergraduate students in STEM and b) building the PI’s research capacity in statistical modeling. To achieve these goals, the PI will complete statistical courses and work with a mentor team to be able to build complex statistical models that explicitly incorporate, rather than ignore, variables related to individuals’ experiences and backgrounds into statistical modeling. This is important because otherwise it can be easy to focus on factors related to the most common participant experiences, rather than capturing the breadth of participant experiences. Important persistence factors may not be identifiable if variables related to experiences and background are not included in models. The PI will use data collected by the non-profit Higher Education Research Institute (HERI) about the experiences of undergraduate students as they enter and graduate from college, as well as institutional characteristics. These models will provide information about the underlying factors that may influence the differences in the persistence of students in different STEM and non-STEM fields, addressing a significant and fundamental issue in STEM education research. In 2015–2019, HERI increased the breadth of their data collection, thus the PI is situated to make key contributions through analyzing this expanded dataset across several cohorts of students. This research will seek to a) help advance the field of STEM education through furthering understanding of the factors that influence student persistence in STEM and provide pathways for positive change; and b) positively impact STEM fields and benefit society through identifying ways to increase STEM persistence by addressing gaps in persistence. The goals of this project are a) capacity-building in statistical modeling for the PI, and b) knowledge-building about factors influencing student persistence in STEM. To build research capacity the PI will complete statistical coursework and work with a mentor team, which will allow the PI to use Hierarchical General Linear Models and Structural Equation Modeling in analyses of the U.S.-wide data from HERI, specifically the Freshman, College Senior, Staff, and Faculty Survey data collected from 2015-2023. These analyses will include variables such as student GPA, academic preparation, academic behaviors, sense of belonging, values, and personal experiences as well as institutional characteristics. The project will uniquely contribute to knowledge about the factors that predict student persistence in STEM by investigating several complementary threads. First, is to compare student persistence across categories of fields of study (e.g. business, English, life sciences, physical sciences), to help understand patterns of persistence relating to characteristics of different fields. Second, is to draw across student, faculty, and staff perceptions of institutional climate, which will provide perspectives on how well aligned these perceptions are within an institution. Third, is to integrate a range of carefully selected variables that characterize student experiences prior to and during their time as undergraduate students, as facilitated by the expanded variables that HERI began collecting within the last decade. Fourth, is to use effect codes for categorical variables with three or more categories instead of indicator variables, which allows all individual subgroups to be compared to the overall group mean, rather than using a reference group. This four-pronged approach will allow the PI to contribute knowledge by identifying leverage points for increasing student persistence in STEM related to specific subsets of student experience and student and institutional characteristics, which would be otherwise unidentifiable. The project is supported by NSF’s EDU Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators’ capacity to carry out high-quality STEM education research. 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.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY/ABSTRACT This proposal will causally test how hormones affect the development and activation of the neural circuitry that drives auditory processing. In humans and other vertebrates, major life transitional events such as development and reproduction are driven by changes in levels of circulating hormones which can impact hearing. Sex steroids like estrogen and testosterone have been shown to have differential effects on hearing sensitivity in adults, while thyroid hormone and glucocorticoids affect infant development and hearing loss in children. Hormone systems are thus becoming targets of therapeutic interventions aimed at improving the quality of life for the approximately 1 in 4 humans that have some level of hearing loss. These therapies can be used to enhance peripheral auditory system function, but their direct impacts on central auditory processing neural circuits is less clear. Understanding the mechanisms through which neuroendocrine systems shape plasticity in auditory function during development and reproduction will provide crucial insights into hormone-mediated hearing loss. The proposed research combines molecular and electrophysiological approaches to examine the basis of neuroendocrine modulation of auditory processing during reproduction and development. Harnessing the well characterized sex-specific acoustically-guided behaviors of one of nature’s acoustic specialists, the frog, this proposal sets out to test the central hypothesis that plasticity in auditory processing is driven by neuroendocrine systems that acutely modulate molecular and neuronal function. My overall objective is to gain essential knowledge and skills to establish an independent research program that advances our understanding of how the brain organizes and integrates auditory cues across biological timescales. During the K99 phase, I will use Tag-Based-RNA-Sequencing (TagSeq) and multiunit electrophysiology techniques to characterize the molecular profile and neural activity patterns of central auditory processing regions pre- and post-reproduction. During the R00 phase, I will implement the techniques acquired in the mentored phase to examine plasticity within the auditory system over development. These experiments will not only test fundamental hypotheses about hormonal regulation of gene expression and neural circuit activity but will help discover novel molecular mechanisms that are important for reorganizing auditory systems in times of drastic and acute physiological change. This research will serve as a launching point to develop a larger research program that investigates how hormones modulate plasticity of auditory function during development. Investigations into the factors, neural circuits, and genes that regulate auditory processing will provide insights into how hormone signaling impacts, and could potentially help ameliorate, hearing-related disorders.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY Multiple system atrophy (MSA), an invariably fatal neurodegenerative disorder with no disease- modifying therapeutics or biomarkers, is characterized by the presence of pathogenic α-synuclein (α-syn) in the brain. Whether the onset of clinical signs is due to gain-of-function (GOF) deficits arising from toxic protein aggregation or from the loss-of-function (LOF) consequences due to α-syn sequestration remains a subject of debate. My objective is to identify MSA-driven changes in neuronal gene expression that may serve as novel biomarkers. Rather than an either-or scenario, I hypothesize that in MSA patients, a combination of the gain of toxic function of α-syn with the loss of normal function contributes to disease pathogenesis. My approach will draw from the expertise of both my sponsor (Dr. Woerman) and co-sponsor (Dr. Regan) to use an unbiased approach to interrogate the GOF vs LOF debate while also identifying potential quantitative biomarkers for MSA. Specific Aim 1 will identify and interrogate distinct changes in gene expression in response to MSA. I will investigate the effect of MSA-induced changes on neuronal gene expression using RNA sequencing (RNA- Seq) on human iPSC-derived dopaminergic neurons infected with MSA α-syn. I will validate hits via ELISA or Western blot using frozen brain tissue from MSA and control patients. Additional time course studies in a mouse model of MSA will be paired with qRT-PCR to identify genes with altered expression throughout disease, which will determine differentially expressed genes that may be used as quantifiable biomarkers for MSA. Specific Aim 2 will determine the effect of MSA on RNA stability. In light of recent findings demonstrating that α-syn interacts with P-bodies, I hypothesize that α-syn accumulation in MSA affects mRNA stability, leading to LOF deficits through altered gene expression. I will test this hypothesis by infecting human iPSC- derived dopaminergic neurons with MSA α-syn and then performing an ActinomycinD pulse time-course assay to measure the decay rate for mRNA. RNA-Seq will then be used to determine differentially expressed genes due to altered mRNA stability. Together, these studies will provide critical knowledge about the consequences of α-syn sequestration on mRNA stability and neuronal gene expression. Given the lack of biomarkers, diagnostics, or disease-modifying therapeutics for MSA, this work will enable future studies focused on MSA patient stratification and the development of a quantitative biomarker that can be used to determine therapeutic efficacy in clinical trials.

NIH Research Projects · FY 2025 · 2024-12

Project Summary Multiple Sclerosis (MS) is the most common neurodegenerative disease affecting young adults, with the average onset at 31 years of age. This is pertinent because the over 2 million people with MS (PwMS) are likely to experience the effects of the disease for approximately half their lifespan. Walking difficulties are a common challenge faced by PwMS, leading to an increased risk of falls, musculoskeletal injury, and a reduced quality of life. More specifically, most PwMS experience significant gait asymmetries between their legs. Split-belt treadmill training, where the speed of each leg is controlled independently, improves gait symmetry in PwMS, Parkinson’s disease, and stroke. Additionally, sensory feedback augmentation produces improved gait performance and motor coordination within these populations. However, there is limited research investigating the neural mechanisms underlying these gait adaptations and whether sensory augmentation can elicit enhanced adaptation during split-belt treadmill training. The objective of this project is to identify the neural underpinnings of split-belt treadmill training and test the efficacy of transcutaneous electrical nerve stimulation (TENS) to further improve gait adaptability. It is hypothesized that participants will have heightened activity in the cortical sensorimotor integration regions during split-belt treadmill training, compared to when the belts are moving the same speed. Additionally, it is hypothesized TENS will enhance gait adaptability during split-belt treadmill training. In this F31 proposal, the candidate, Andrew Hagen will recruit 30 PwMS and 30 neurotypical controls. Participants will undergo split-belt treadmill training while cortical activation is measured using functional near- infrared spectroscopy (fNIRS). Separate split-belt treadmill training sessions will also utilize the application of TENS, and the effects on gait adaptability will be assessed using kinetics and kinematics. By enhancing our understanding of the underlying neural mechanisms and evaluating sensory augmentation to enhance split-belt treadmill training, this project aims provide a significant step toward creating a targeted rehabilitation paradigm to improve gait symmetry long term that would improve mobility, independence, and quality of life for not only PwMS but the tens of millions of people who experience gait dysfunction. Mr. Hagen’s long-term goal is to become an academic, translational scientist investigating neural injury rehabilitation. Mr. Hagen will train in a state-of-the-art environment with an exceptional mentoring team at Colorado State University. The sponsor, Dr. Brett Fling, has an extensive background studying sensorimotor control and adaptation in PwMS. Consulting mentors Drs. Jaclyn Stephens and Mark Manago will provide expertise on functional neuroimaging and translational research to prepare Mr. Hagen for a career as a translational scientist. Mr. Hagen’s career development plan consists of 1) training in neuromechanics and neuroimaging, 2) strengthening his background in neural injury rehabilitation methods and clinical application, and 3) further developing his professional and communication skills through interaction with his mentors, coursework, clinical exposure, and conferences.

NSF Awards · FY 2024 · 2024-12

Many modern real-world manufacturing and scheduling problems need to satisfy multiple goals. For example, in automotive design we would like to increase safety and fuel efficiency, while at the same time decreasing cost and harmful emissions. However, a good solution must balance these conflicting goals. The need to balance conflicting goals is common across virtually all industrial and engineering problems. Traditional optimization tools are designed to achieve the best possible outcome for one goal, but do not work well when solving for multiple goals. Modern multiobjective methods are increasingly being used by industry but are not as well understood as single objective methods. Part of the problem is that there is not a single best solution, but rather there will be a family of solutions representing the possible trade-off between different goals. In shipping and logistics, we want to ensure on-time arrival of goods, while also minimizing shipping costs and the risk of shipping disruptions. But, if one solution reduces average shipping cost, while another solution reduces the risk of disruption, which is the right answer? Multiobjective tools do not provide a best solution, but instead give a human decision maker a family of options to select from, which highlights the trade-offs between the different conflicting goals. This project will improve multiobjective optimization tools. The family of best solutions under multiobjective optimization form what is known as a Pareto Front. Given two solutions that lie on the Pareto Front, how do we efficiently find other solutions that also lie on the Pareto Front? Most current multiobjective optimization tools are highly stochastic in nature. This project exploits new mathematical methods that have the potential to deterministically explore the Pareto Front. These new methods take two (locally optimal) solutions and then remove all nonlinear interactions in each evaluation function that are not locally relevant to these two solutions. The nonlinearity of the evaluation function in this lower dimensional space is guaranteed to be less than (if not equal to) the nonlinearity of the full space. Simplifying the evaluation function in the lower dimensional space will often decompose the full evaluation function, causing it to become locally linearly separable in the reduced space. When this occurs, we can provably generate the best of exponentially many piecewise locally optimal solutions in linear time. We have already shown this method works extremely well on classic NP-Hard problems. If we take two solutions on the Pareto Front, we can also define a lower dimensional space between pairs of solutions. Given two solutions, this gives us a highly efficient deterministic method to search for other solutions that potentially lie along the Pareto Front. Our work will also look at hardware and software innovations as well as parallel implementations to support our new multiobjective optimization tool. This project is a collaboration between a French and US Investigator under the CISE-ANR funding agreement. 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 · 2024-12

Many of the key challenges facing society – such as enhancing human health, conserving biodiversity, and improving domesticated species – can be addressed through a better understanding of genetic variation. Luckily, genetic tools, like genome sequencing, gene editing, and robotic trait measurements, have advanced rapidly in recent decades. But genetic theory has not kept pace with discoveries on the molecular and cellular basis of organisms’ traits. Instead, the standard theory that geneticists use to try to understand quantitative genetic variation and predict its effects is largely from the first half of the 1900s, and it ignores insights from molecular and cellular biology. Recently, however, geneticists have been exploring exciting new models of genetics, which better incorporate biological knowledge into quantitative trait genetics. This project will develop new tools for geneticists to incorporate these emerging new models in genetics into their research, and rigorously test the underlying concepts. The tools will be tested in laboratory plants and in crops, which are ideal systems to develop and test concepts and tools that can later be used in hard-to-study organisms, such as humans or wild organisms. This project will directly benefit society by making new tools for genetic mapping, prediction, and simulation available to global crop improvement programs; as well as improving both the understanding of genetics and the scientific method in public-school students and trainee scientists. Understanding the genetic architecture of complex quantitative traits is a central goal of biology. However, standard quantitative genetic theory and practice does not incorporate molecular and cellular biology knowledge, such as gene expression patterns and gene regulatory networks. Further, existing tools do not provide functionality to test emerging models, such as the omnigenic model. The goal of this project is to develop genetic analysis tools that incorporate molecular and cellular biology knowledge directly into statistical models used to map genes, predict traits, and simulate changes in the genotype-to-phenotype relationships. These tools will be used to test the hypotheses on the impact of various forms of gene interactions (epistasis) and test the hypothesis that the omnigenic model accounts for differences in genetic architecture of traits across subpopulations. This research will provide insight into how and why genetic architecture differs across subpopulations, a key question in several areas of basic and applied genetics. Research will be conducted using simulated traits as well as real genotype and phenotype from the model plant Arabidopsis thaliana and the crop, Sorghum bicolor. The broader impacts of this project will focus on developing both graduate student and high school level activities that teach fundamental concepts in genetics and scientific method. This project will also work with public crop breeding programs to ensure that the research findings will be diffused to the applied plant genetic community. 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 · 2024-12

Changing climates are a major challenge for humans and nature. One of the most important scientific questions of the 21st century is "What will determine the vulnerability of species and biological communities to environmental disruption?" Addressing this question, however, is extremely challenging because changes in climate are complex, evolutionary history will determine species' sensitivity, and species' responses will be affected by the complex food webs of which they are a part. For example, even if a predator species is relatively insensitive to warming temperatures, it may still be vulnerable if the prey species it feeds on are sensitive and disappear. The research team will investigate thermal vulnerabilities of cutthroat trout predators and tailed frog tadpole prey in mountain streams of the U.S. Pacific Northwest using a multidisciplinary approach that combines cutting-edge DNA sequencing technology, physiology experiments, and high-performance computer modeling. This is an excellent predator-prey case study to investigate this question, as cutthroat trout are important predators of tailed frog tadpoles, both species are cold-water specialists that are sensitive to warming, and both species are of conservation concern. Thus, results of this study will be important for informing their conservation and management. The research team will work closely with federal and state natural resource agencies to make sure that results are useful for informing decisions about the conservation and management of stream biodiversity. The team will develop a web-based tool to help managers assess environmental vulnerabilities. The project will also provide training for four early career researchers. It is essential to integrate organismal, ecological, and evolutionary perspectives to predict the vulnerability of species and biological communities to global change. The proposed research will use a highly interdisciplinary approach to test several novel hypotheses about the mechanisms underlying environmental vulnerability in a predator (cutthroat trout) - prey (tailed frog) system in streams of the U.S. Pacific Northwest. In Aim 1, the research team will test whether predators (cutthroat trout) are more sensitive to increasing temperatures than their prey (tailed frogs) using a combination of environmental characterization, genomics, and physiology to quantify thermal adaptation. In Aim 2, they will test whether different dimensions of adaptive capacity (dispersal, evolutionary potential, and acclimation ability) differ between predators and prey by using genomics to characterize patterns and rates of connectivity across the landscape and evolutionary potential, and physiology to quantify acclimation. In Aim 3, the team will determine how predator-prey interactions respond to temperature and flow by quantifying the diet of cutthroat trout and energy content of tailed frogs, and by using a mechanistic food web model to predict how climate change-driven changes in energy flow and food web dynamics will affect cutthroat trout-tailed frog interactions. In Aim 4, they will integrate the results from Aims 1-3 using an individual-based, eco-evolutionary model to predict how species interactions, intraspecific variation in sensitivity, and adaptive capacity act synergistically to determine spatial patterns of thermal vulnerability in cutthroat trout and tailed frogs. 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.

NIH Research Projects · FY 2024 · 2024-11

PROJECT SUMMARY The long-term objective of this application is to revolutionize the treatment of severe traumatic brain injury (TBI) by employing a novel osteogenic hydrogel material in an unprecedented single-stage decompressive craniectomy (DC) procedure. DC is a common life-saving neurosurgical procedure performed on TBI patients with either closed head injury and/or stroke. Removing the cranial bone mitigates rising intracranial pressures by allowing the brain to swell outside the closed calvarial vault. Following the procedure, patients are currently left with a large cranial defect (i.e., a large hole in their skull) for weeks or months and require a 2nd surgery to replace the missing cranial bone with their preserved cranial bone or a custom 3D-printed material. In such cases, this 2nd surgical procedure is currently unavoidable. Our strategy is unique and unprecedented by treating TBI patients with a single-stage surgical procedure. The key to our approach is a new class of hydrogel materials, where natural materials of demineralized bone matrix, devitalized cartilage, or devitalized tendon are themselves the crosslinkers of the hydrogel. Our material consists of a paste-like precursor solution of tissue particles and hyaluronic acid that behaves as a paste that a surgeon can easily sculpt into the open calvarial defect area. With only 2 minutes of UV light exposure the particles are crosslinked with the hyaluronic acid to create a new material that is solid, yet flexible, and can allow the brain to swell initially, and then transition into bone as the brain swelling subsides. The innovation of this material after crosslinking is that it can provide localized relief of swelling by releasing anti-inflammatory molecules to improve and accelerate neurological recovery, and moreover provide a protective layer between the scalp and the body’s most indispensable organ. The chief hypothesis is that our flexible, drug-eluting hydrogel implants placed immediately following TBI and DC in rats will transition to complete bone spanning the cranial defect and mitigate neurologic deficits associated with TBI. To test this hypothesis, the following Specific Aims are proposed: 1) Tune hydrogel stiffness and bone regeneration for application to TBI, and 2) Evaluate localized anti-inflammatory drug delivery after TBI to reduce edema/brain injury volume and thereby to improve behavioral recovery. Our approach is unique in that we are leveraging musculoskeletal regenerative medicine as a tool to usher in a new paradigm for severe TBI treatment. While a primary debate in the neurosurgery field for treatment of TBI revolves around the amount of time between the 1st (DC) and 2nd (cranioplasty) procedures, we challenge whether that debate is even necessary. Instead, we ask whether the 2nd surgery can be eliminated altogether by introducing a dynamic material as part of the first, and only procedure. In so doing, we hold the potential to mitigate neurologic deficits associated with severe TBI with an unprecedented single-stage procedure.

NSF Awards · FY 2024 · 2024-11

NON-TECHNICAL DESCRIPTION: Solid oxide fuel cells based on the conduction of hydrogen ions (called protons) are a type of electrical power generation device that stands to offer much higher efficiency and lower emission than current technologies. Such proton conducting solid oxide fuel cells (PC-SOFCs) can utilize a wide range of fuels from pure hydrogen to readily available hydrocarbon fuels such as natural gas and biogas. This project aims to generate new fundamental knowledge about a very important reaction involving hydrogen gas at the negative electrode of PC-SOFCs at temperatures relevant to operation. It also aims to develop new electrode materials that could further enhance the performance and robustness of PC-SOFCs. Knowledge from this project can be leveraged to other applications such as electrochemical energy storage, chemical production, and sensors. The project promotes education in advanced ceramic materials at Florida International University (FIU) and the broader southern Florida region through various education and outreach activities. TECHNICAL DETAILS: Despite the advantages of PC-SOFCs such as higher theoretical efficiency and potential for reduced degradation, many fundamental aspects are not known. This project aims to generate new knowledge about the very important hydrogen electrode reaction for PC-SOFCs using a combined set of technical approaches. For example, PC-SOFC button cells with patterned metal electrodes are used together with theoretical modeling to reveal the linkage between hydrogen electrode reaction kinetics and electrode geometry. Study of the impacts of fuel contaminants (e.g., hydrogen sulfide) help clarify the origins and the limitations of PC-SOFCs' intriguing electrochemical behaviors such as better sulfur tolerance. These studies also provide insights about the underlying hydrogen electrode reaction mechanism. On the other hand, new hydrogen electrode materials are designed via catalyst infiltration or exsolution techniques. Tailored doping of highly conductive oxides is being carried out to achieve mixed proton-electron conduction or better tolerance to fuel contaminant (e.g., carbon dioxide) for further improved PC-SOFCs. The education and outreach activities aim to raise awareness and interest, enhance access to related knowledge, and provide engagement in research for students (especially minority students), with these efforts centered around advanced ceramic materials. For example, video recording of lectures and important lab procedures are provided on the web. In addition, mobile social networks tools such as WhatsApp are actively adopted for communication. 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 · 2024-11

This workshop has been organized to investigate the state of knowledge about bioaerosols in the Earth system. Many gaps exist in the basic understanding of factors that shape the microbial composition of ambient bioaerosols and their resultant impacts after transport in the atmosphere and deposition to the surface. The goal of this workshop is to leverage the expertise among the diverse participants to distill recent findings, discover synergistic approaches and innovative solutions to tackle difficult but critical scientific gaps, and provide their expert opinions on the most compelling research opportunities that will lead to high impact scientific discovery and advancements in the knowledge about bioaerosols in the Earth system. Three co-chairs from the fields of atmospheric science, biological science, and engineering represent the multidisciplinary aspects of the issue of bioaerosols and will serve as organizers of the conference. The findings from this workshop will serve to highlight gaps in understanding, observations, technology, and predictive capabilities that are hindering scientific progress, and will be disseminated to encourage new interdisciplinary research aimed at filling these gaps. The co-chairs plan to communicate workshop findings in the peer-reviewed literature. This workshop is supported by the following programs at NSF: Atmospheric Chemistry and Physical and Dynamic Meteorology in GEO; Population and Community Ecology Cluster, Ecology and Evolution of Infectious Diseases, Ecosystem Science, and Symbiosis, Infection and Immunity in BIO; and Nanoscale Interactions, Environmental Engineering, and Environmental Sustainability in ENG. 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 · 2024-10

Static Random Access Memory (SRAM) used in computing systems is subject to data imprinting, where information stored in the memory persists even beyond the lifetime of system use. Data imprinting effects on commercial SRAM pose a significant security risk for modern computing systems. These effects can cause the persistence of sensitive information in memory beyond its intended use. For instance, when electronic systems are discarded, there is a noteworthy chance that the SRAM memory remains operational, creating a risk of leaking previously stored sensitive information and leading to unauthorized access and compromise. This underscores the critical necessity for implementing robust sanitization measures to securely dispose of electronic systems and mitigate the potential risks associated with the persistence of sensitive information in SRAM memory. This research project investigates the potential of data retrieval from used SRAM chips that have been discarded without awareness of the threat of sensitive information recovery. The team has demonstrated that the information imprinted on these chips is long lasting, underscoring the need for thorough data sanitization to prevent unauthorized access. Additionally, the project develops a novel data sanitization technique for SRAM memories that will benefit consumers, industry, and government alike by ensuring that deleted data is not recoverable at any time during the product’s life cycle. A direct outcome of this project is training two graduate students in the important area of hardware-oriented security and radiation effects on microelectronics. Recent studies have demonstrated that data imprinting effects influence the power-up state of an uninitialized SRAM array, potentially enabling adversaries to recover sensitive information. The project focuses on an in-depth analysis of the security threats posed by SRAM data imprinting effects. The team focuses on the real-world scenarios where attackers could exploit these vulnerabilities to gain unauthorized access, manipulate sensitive data, or launch other malicious activities. Additionally, the project explores new, cost-effective data sanitization techniques tailored for SRAM memories. Overall, the project characterizes the effectiveness of data recovery from SRAM memory under various usage conditions. The team evaluates the efficiency of data recovery techniques on different types of SRAM memories across diverse technology nodes and develops cost-effective techniques for data sanitization utilizing high-energy irradiation. Experimental assessment is performed to examine the effectiveness and resilience of these techniques against resourceful malicious data recovery efforts across a range of operating conditions. 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 · 2024-10

The Louis Stokes Alliances for Minority Participation (LSAMP) program assists universities and colleges in their efforts to significantly increase the numbers of students matriculating into and successfully completing high-quality degree programs in science, technology, engineering, and mathematics (STEM) disciplines to diversify the STEM workforce. LSAMP considered EArly-concept Grants for Exploratory Research (EAGERs) under NSF 24-1 to support early concept broadening participation research with the potential to have transformative impacts on undergraduate STEM education. This exploratory research project leverages large language models to assist in the content analysis of qualitative data gathered from underrepresented students in STEM disciplines. The study takes an ecosystems model of STEM education, which characterizes students as decision makers in environments that actively attract or repel them. This perspective suggests degree persistence, or the continued pursuit of a STEM degree once declared, is influenced by factors at multiple levels – including the individual, their immediate academic environment, and their institution. The project seeks to refine this emerging methodology by co-developing thematic codes with large language models, which will then be applied to analyze a large corpus of student narratives. By doing so, the research will reveal environmental determinants of STEM degree progression, specifically focusing on how these determinants vary across different institutions and majors. The findings will inform strategic interventions ultimately contributing to broader efforts to increase diversity in STEM. 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 · 2024-10

U.S. cities remain slow to respond to the impact of climate change due to limited staff capacity, difficulties with community buy-in, and gaps in knowledge. One of the most critical biodiversity losses related to climate change has been the decline of insect pollinators, due in large part to their lack of healthy habitats. Pollinators play an important role in providing natural benefits to cities' urban food systems. The loss of pollinators may limit cities’ ability to implement natural climate solutions as that loss could hamper the success of green infrastructure initiatives that rely on plants. Increasingly, scientists and the public are realizing the benefits of pollinators in their communities. This project team will co-create data, tools, and engagement actions on climate-resilient pollinator habitats with communities across the city of Denver, CO. Working with frontline communities most affected by climate change and nature loss is a central aim of this project. The vision of the project is to facilitate community partners’ ability to identify, analyze, and prioritize existing spatial gaps in climate resilient landscape across the whole urban matrix of Denver and improve Denver’s climate resiliency by developing data to fill information gaps and research tools to aid decision making around community-driven project implementation. The project team will combine a genetic marking technique for insects with conventional GIS spatial data to provide a spatially explicit prioritization of significant gaps in the Denver urban matrix where landscape changes would benefit biodiversity, pollinators, residents, and overall climate resiliency. The team will directly measure pollinator and community response to experimental climate-resilient habitat installations that use optimized plant mixes developed by a plant selection tool from a prior pilot study. Working with partners, the research team will identify plots where habitats can be transformed with the plant mixes and measure both pollinator attractiveness and how the relevant community responds to the transformations. Creating research products that empower local community members and organizations is a central aim of this research project. This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. 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 · 2024-10

Landslides are a major geo-hazard causing significant casualties, infrastructure damage, and economic losses worldwide. With the increasing frequency of extreme weather events, many communities are facing increasing risk of landslides. However, many rural, isolated, and small communities (RISC) communities lack the knowledge and tools to prepare for and mitigate landslide impacts. This project seeks to establish robust community partnerships, engage community members through collaborative workshops and focus groups to identify their needs and priorities related to landslide risks, co-produce research questions and solutions. These foundational efforts are crucial for creating a comprehensive, community-driven research initiative that leverages advanced earth system science to enhance resilience and provide actionable solutions for mitigating landslide hazards. This project will help enhance community resilience in areas disproportionately affected by landslide hazards. It will also provide valuable research and educational opportunities for local citizen scientists from underrepresented backgrounds for building capacity in the community. This project aims to address significant knowledge gaps in landslide risk propagation, perception, communication, and mitigation for underserved rural, isolated, and small communities. This project will engage RISC communities in Southwestern Puerto Rico and establish robust community partnerships. The primary objectives of this project are: (1) Establish new collaborations with essential federal and local partners. These partnerships will facilitate access to critical data, resources, and local knowledge to support coordinated responses to landslide hazards. (2) Co-produce research questions and solutions. This project will engage community members through surveys, interviews, and collaborative workshops, and focus groups to identify their needs and priorities related to landslide risks, co-produce research questions and actionable solutions. This participatory approach will ensure that the research questions and solutions developed are grounded in real-world experiences and directly address community concerns. (3) Establish feedback channels and protocols to continuously gather input from stakeholders and community members. By building the necessary connections to confront landslide hazards and build resilient communities, this project will lay the foundation to advance the scientific understanding of risk propagation of landslide-community systems and support effective community-centric risk mitigation strategies customized to the local social and cultural context. The project results are expected to inform the adaptation and application in other regions facing similar hazards, amplifying its impact beyond Puerto Rico. 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 · 2024-10

Communication is the top job skill required across all sectors, and ethical science communication (scicomm) helps scientists identify and engage with the values, needs, and diverse ways of knowing of people ranging from community members to policy makers. Graduate students themselves have identified the need for training in these translational skills before embarking on their post-graduation careers. Yet, most scientists receive no formal training in scicomm and report feeling ill-equipped to share science effectively. Scicomm training is not widely embraced in academia due to systemic barriers that impede and devalue both study and training in scicomm. Working at an unprecedented scale, SciComm LIFT will survey, train, and support thousands of graduate students -- across the country and across institution types -- for the top skills required by employers: oral and written communication and collaboration. SciComm LIFT's emphasis on ethical scicomm training will also directly enhance graduate degree programs and professional development programs, ensuring early career scientists are more capable of doing and sharing science in ways that meet the needs of society and foster public trust in and of science. SciComm LIFT uses expectancy values theory to address three issues: (1) most scicomm training programs prioritize knowledge gains and skills, but ignore the human/ethical elements of scicomm that are vital to science that fosters public trust; (2) existing scicomm training is rarely assessed, making it difficult for trainers and programs to optimize programming and demonstrate its efficacy; (3) long-standing, systemic barriers impede integration of ethical scicomm training. In Aim 1, SciComm LIFT will conduct a broadly distributed, systems-scoping survey (Motivations to Engage in Scicomm Advancement; MESA) of graduate students, faculty, and staff to (1) assess current knowledge, motivations, and self-efficacy around ethical scicomm and (2) quantify the extent of training addressing ethical dimensions of scicomm. MESA will be made available to the research and graduate education community as a validated, reliable instrument tested across contexts and institutions. Aim 2 is a multi-institutional study to gauge the impact of three ethical scicomm interventions in graduate programs, which will provide much-needed data that can be used to calibrate scicomm training programs nationwide. Aim 3 investigates how three levels of coaching can support academic faculty and staff to overcome institutional barriers preventing them from offering ethical scicomm training to graduate students. These aims will benefit society by preparing graduate students to bridge the divide between science and society through effective, ethical communication. The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community. 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.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Aging increases the risk for Alzheimer’s disease (AD), but as described in NOT-AG-21-039, the underlying mechanisms are poorly understood. In this R21 project we propose to test the efficacy of a novel therapeutic targeting neuroinflammation for protecting against brain aging and AD-related pathology, and to evaluate the role of the key neuroinflammation mediators NF-κB and NLRP3 in this context. Our rationale is based on pilot studies we performed using NF-κB/NLRP3-targeted Nanoligomers, a novel class of clinically translatable small molecules that specifically downregulate gene targets of interest. Our pilot data show that Nanoligomers targeting NF-κB and NLRP3 have the potential to reduce neuroinflammation, enhance memory (one key domain of cognitive function that declines with aging and predicts AD risk) and favorably modulate the brain transcriptome in both aging wild-type mice and a transgenic, AD-relevant mouse model. Based on these observations, we propose a series of comprehensive pre-clinical studies in which we will test the efficacy of NF-κB/NLRP3-Nanoligomers for reducing neuroinflammation and protecting different domains of cognitive function with aging vs. AD-related pathology by administering NF-κB/NLRP3-Nanoligomers to: 1) old wild-type mice; and 2) transgenic mouse models of both amyloid beta (Aβ) and tau pathology (the main pathological features of AD). In all models, we will conduct a battery of cognitive-behavioral tests to comprehensively evaluate the functional effects of NF-κB/NLRP3-Nanoligomer treatment, and we will perform brain region- specific transcriptomics (RNA-seq) and analyses of numerous neuroinflammation and pathological markers. We also will perform 3) a series of complementary bioinformatics analyses using existing human datasets to determine if there is greater evidence of NF-κB/NLRP3-associated neuroinflammation with aging vs. pathology in the human brain. Together, the results of these experiments will allow us to determine the ideal application of NF-κB/NLRP3-Nanoligomers (i.e., prevention during aging vs. treatment of pathology), and to establish evidence for the role of NF-κB/NLRP3-associated neuroinflammation in these specific contexts (an important question in research on brain aging and AD). Our aims are specifically designed to enable a future R01 project, as they will provide a basis for larger studies aimed at understanding age- vs. pathology-related neuroinflammation and insight into how and when to administer Nanoligomers in pilot clinical trials.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Over 7 million Americans currently suffer from a neurodegenerative disease (NDD), including Alzheimer’s disease and multiple system atrophy. In these disorders, intrinsically disordered proteins, including tau and α-synuclein (α-syn), misfold into a prion-like conformation capable of self-templating and spreading throughout the brain, causing progressive degeneration. Although age is the greatest known risk factor for the onset of NDDs, we urgently need to understand the mechanisms by which treatable risk factors contribute to disease, including sleep and circadian clock disruption. It is well established that sleep disruption impairs autophagy, whereas promoting autophagy via small molecules, such as rapamycin, delays disease onset in animal models of NDD. Given the growing literature identifying poor sleep quality and sleep disorders as both a preclinical sign and a symptom of NDDs, there is an increasing need to determine if protein misfolding leads to sleep and circadian desynchronization, if environmental circadian desynchronization (ECD) leads to protein misfolding, or if both occur in a positive feedback loop that is mediated via impaired autophagic activity. The long-term goal of our research is to understand the shared molecular mechanisms that contribute to the onset and progression of NDD. Our objective is to establish the mechanism(s) by which disrupted sleep and circadian timing contribute to the formation and spread of pathogenic tau and α-syn in the brain. We hypothesize that the effects of circadian clock disruption on tau and α-syn spreading in NDD are mediated by altered autophagic activity in the brain. Rather than a linear signaling pathway, we anticipate that ECD sits atop a positive feedback loop exacerbated by the presence of pathogenic protein in the brain. Our approach will investigate the bidirectional nature of this relationship. In Aim 1, we will investigate the effect of tau and α-syn propagation on sleep and circadian rhythms, and will determine if enhancing autophagy can slow these effects. In Aim 2, we will interrogate the effect of circadian clock manipulation on the onset and progression of NDD. We will also determine if ECD impairs autophagic activity to accelerate protein misfolding in the brain. While epidemiological and experimental studies have shown a clear interaction between circadian rhythms and NDDs, the nature of that relationship remains unclear. Successful completion of the proposed studies will determine if NDD drives circadian and sleep disruption, if ECD can drive NDD, and/or if the two exacerbate one another through a positive feedback loop. Notably, because this proposal draws on Dr. Woerman’s expertise in tau and α-syn misfolding in NDD and Dr. Karatsoreos’ expertise in circadian clock regulation of brain function, we are uniquely positioned as a multi-PI team to address this important question.

NSF Awards · FY 2024 · 2024-09

This project, a collaboration of mathematicians, data scientists, and atmospheric scientists, seeks to gain a deeper understanding of the formation of clouds and storms in both the present and future climate of our planet. To do this, the project will develop novel algorithms leveraging recent advances in Artificial Intelligence (AI) and advanced mathematics that are contributing to the creation of Interpretable AI, in which AI models and their outputs are more human-understandable. The anticipated benefits for public safety are twofold: (1) to improve the prediction of hazardous weather conditions in the present time, and (2) to better understand hazardous weather conditions in the future climate, thus providing much needed information for policy decisions. This work will assist in developing a globally competitive STEM workforce by training several scientists in the development of mathematical and AI approaches and their use for geoscience applications. Additionally, this project is expected to lead to new connections between mathematical methods and geoscience applications which will bring new opportunities to both fields. This project has several goals and associated activities. The first goal is to gain a better understanding of the connections between large-scale environmental characteristics from reanalysis products and smaller-scale satellite-derived estimates of cloud properties. The proposed approach aims to use relatively simple and interpretable AI models to create a mapping between these two datasets. This mapping will be used to study current cloud variability overlapping with the satellite record and estimate historical cloud variability before the satellite era. The second goal is to discover how large-scale environmental variables, which cannot show detailed weather processes, relate to finer-scale elements like the three dimensional structure of clouds and precipitation, especially in a future warmer climate scenario. The proposed approach is to combine mathematical and AI methods to analyze climate model simulations for current and future climates to connect broad environmental conditions with specific cloud features. This activity will help prepare for the future climate, benefiting society by enhancing understanding of weather patterns and their impacts. The third goal is to develop Interpretable AI methods by integrating mathematical components, including mathematical feature engineering using equi-/invariant mathematical frameworks, such as topological data analysis and harmonic analysis. These research activities are expected to lead to new connections between mathematical methods and geoscience applications, bringing new opportunities to both fields. Furthermore, expanding the use of mathematical methods to make AI models more interpretable creates new opportunities to use AI methods for knowledge discovery in a wide range of geoscience applications. This award by the Division of Research, Innovation, Synergies, and Education within the Directorate for Geosciences is jointly supported by the National Discovery Cloud for Climate initiative of the Office of Advanced Cyberinfrastructure within the Directorate for Computer and Information Science and Engineering and by the Division of Mathematical Sciences within 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.

NIH Research Projects · FY 2025 · 2024-09

Abstract Down syndrome (DS) predisposes individuals to a wide range of cognitive outcomes, with some individuals acquiring more advanced cognitive skills and others demonstrating severe or profound levels of intellectual disability (S/PID). The early origins of S/PID in individuals with DS are poorly understood, and individuals with DS and S/PID are often underrepresented in the scientific literature. This project will address an important gap in our knowledge and establish a novel account of variability in cognitive skill acquisition in DS with an emphasis on understanding those children who demonstrate the most pronounced levels of early cognitive delay. We will characterize early cognitive growth in young children with DS and examine the association between severe/profound early cognitive delays and behavior, biomedical factors, and molecular biosignatures known to be affected by DS, such as various inflammatory processes, elevated neurodegeneration and neuroinflammation biomarkers, dysregulation of the growth hormone (GH)-IGF1 axis, and dysregulated metabolism. To achieve this goal, we will recruit 90 children with DS to be assessed at three data waves (Wave 1 = 12 months; Wave 2 = 24 months; Wave 3 = 36 months) and we will conduct comprehensive cognitive and broader developmental evaluations. Blood samples will be collected concurrently with each visit and biomedical history information will be obtained. We will then model latent growth trajectories along early cognitive and other developmental domains and examine the association between growth profiles, biomedical history, molecular biosignatures, and severe/profound degrees of early cognitive delay at Wave 3. This integrated approach to characterizing heterogeneity in cognitive delays in DS can potentially transform the nature of treatments and interventions for those individuals who are in need of the most intensive degree of lifelong community support.

NSF Awards · FY 2024 · 2024-09

Given the persistent challenge of racial inequity in STEM, there is a clear need for new models that spur and sustain racial equity change. Successful departmental team-based change efforts demonstrate that change can be created and sustained at the meso level of an institution (i.e., departments, centers, and units as the focus for change). This project will bring together experts in institutional change and experts in advancing racial equity with the goal of combining existing, well tested change models to produce a new, racial equity focused model of change in higher education—the Equity Departmental Action Team (EDAT) model. This model will focus on shifting departmental cultures in ways that benefit, and are grounded in the experiences of, those with historically marginalized racial and ethnic identities. This project will advance the scholarship of racial equity by developing, testing, and refining the EDAT model with STEM departments at a Minority Serving Institution and disseminating the model through partnership with national higher education associations. This project will take place in two major phases: 1) development of the Equity Departmental Action Team (EDAT) model, and 2) pilot of the EDAT model in STEM departments at a Minority Serving Institution, the University of Colorado Denver (CU Denver). The development of the new EDAT model will draw from existing change programs, including the Departmental Action Team (DAT) model and the Dialogues and Change Agent programs. It will integrate multiple theories from systems change, social justice change, social psychology change agency, and intergroup contact. Research activities will focus on both the process and impact of the EDAT model. The project will use surveys, focus groups, interviews, and participant journaling to explore the following research questions. RQ1: To what extent do Foundational Experiences prepare EDAT members for racial equity work? RQ2: What strategies do EDATs deploy when engaging in racial equity work? RQ3: To what extent do EDATs integrate racial equity into departmental culture? Research and program evaluation will be conducted simultaneously with the EDAT implementation so the model can be iteratively refined throughout the project. Dissemination of the model will take place in collaboration with partners from the American Association of Colleges and Universities and the Coalition of Urban Serving Universities - Association of Public and Land-grant Universities. This collaborative project is funded through the Racial Equity in STEM Education activity (EDU Racial Equity). The 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. Awarded projects seek to center the voices, knowledge, and experiences of the individuals, communities, and institutions most impacted by systemic inequities within the STEM enterprise. This activity aligns with NSF’s core value of supporting outstanding researchers and innovative thinkers from across the Nation's diversity of demographic groups, regions, and types of organizations. 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

The iconic American Bison (Bison bison) has historically played an important role in North American grasslands, particularly those known as Great Plains grasslands of central North America. Although bison ranged well beyond the Great Plains, knowledge is limited of their effects in these other grasslands. Therefore, the full effects of large-scale removal of bison from the grasslands of North America are unknown. With new efforts to reintroduce bison to their historic habitats, there is a pressing need to understand the effects of these reintroductions. In 2024, the Blackfeet Tribal Nation in Northern Montana is planning to reintroduce free-roaming bison to 26,000 acres of montane fescue grasslands ~150 years since their extermination. This event provides a unique opportunity to examine how bison affect several aspects of ecosystem structure and function, as well as plant species composition. This project has been designed in collaboration with the Blackfeet Department of Fish and Wildlife and Blackfeet Community College, who play important roles in the research. Further, this project provides improved ability to predict bison grazing effects on plant communities in other reintroduction efforts. A grazing experiment in a previously unstudied montane grassland provides data about one of the largest bison restoration efforts on Tribal lands and the North American continent. In collaboration with the Blackfeet Community College, large, fenced exclosures have been established that prevent bison from accessing grassland areas that then can be compared to nearby areas that are open to bison grazing. Both of the grazed and ungrazed areas will be surveyed for plant species and abundances, annual net primary productivity (ANPP, a common measure of plant growth), and nutrients in plant tissues and soils. Collectively, these data will provide a baseline understanding of these grassland plant communities prior to bison reintroduction, allowing Blackfeet Tribal Nation managers to monitor grasslands into the future and researchers to examine over time the effects of bison reintroduction in a previously unstudied fescue grassland. 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 research aims to explore how wealth and other socioeconomic factors affect biodiversity in cities. Urban areas contain a significant amount of biodiversity, including 20% of the world's bird species and 5% of its plant species. However, biases in how ecological data are collected often hide the true distribution of urban wildlife. Wealthier urban neighborhoods often have more parks and green spaces, which can lead to greater diversity of plants and animals compared to lower-income areas. Yet, this pattern may be affected by biases that favor data collection in wealthier neighborhoods. Understanding urban ecology requires accurate data that capture the complex interactions between humans and nature. One way that this is done is through citizen science. Citizen science involves the public in collecting ecological data. This allows researchers to study social and ecological patterns across multiple cities. For example, the eBird project records millions of bird sightings each year. But, eBird data may be biased towards wealthier areas, potentially overestimating biodiversity compared to less affluent neighborhoods. The project will reduce these biases by analyzing data from diverse urban neighborhoods across multiple cities. The researchers will use these data to test how social and economic factors affect biodiversity patterns. By understanding these relationships, the research will address how cities affect ecological patterns and the drivers of biodiversity in urban settings. The research will also enhance citizen science's role in urban ecology by reducing bias in these datasets. The results will be important for understanding urban ecology and promoting social and environmental justice. More accurate assessments of biodiversity are essential for urban planning and conservation efforts, benefiting both wildlife and human communities. Additionally, the project will train students, including those from underserved communities. The research will expand a framework designed to mitigate sampling bias in citizen science data, focusing on understanding factors influencing the socioeconomic status (SES) and urban biodiversity relationship. The project aims to achieve three objectives: 1) Identify and quantify SES-related biases in citizen science datasets using eBird observations and a reference dataset of bird observations from underrepresented neighborhoods to fill sampling gaps; 2) Assess SES-biodiversity relationships after accounting for these biases; and 3) Evaluate how SES, built environment characteristics, and natural factors shape biodiversity across multiple cities, providing insights into urban biodiversity drivers. Our approach will apply a preferential sampling model from spatial statistics literature to jointly model species occupancy, spatial sampling intensity, and their relationships, enabling a comprehensive assessment of biodiversity patterns and sampling biases. By challenging assumptions about SES-biodiversity relationships and evaluating how socioeconomic factors interact with the built environment and natural features, this research aims to provide a clearer understanding of urban ecological dynamics, potentially reshaping theoretical frameworks and guiding future research in urban ecology and citizen science, while improving the reliability of biodiversity assessments crucial for urban planning and conservation strategies. 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

For this project, the PI and collaborators will perform high-precision, quantum-enabled laser spectroscopy experiments on trapped, highly charged ions for the purpose of testing fundamental physics at low energy. Highly charged ions (atoms in which several electrons have been removed) are among the most sensitive systems to a possible time-variation of the fundamental physical constants. This high sensitivity, combined with laser-accessible transitions, makes them a unique platform for investigating predicted extensions to the standard model of particle physics. This project will focus on the development of an optical atomic clock based on trapped highly charged metal ions. The experiment will combine techniques that have been developed for ion trap-based quantum computing and optical frequency standards with a compact source of highly charged ions. This project will also provide training for undergraduate and graduate students in the fields of experimental atomic, molecular and optical physics, optical frequency metrology, and precision measurements. Several optical transitions in highly charged ions provide both an enhanced sensitivity to possible time-variation of the fine-structure constant (alpha) and favorable systematics as optical clocks when compared to singly charged ions and neutral atoms. In particular, these systems are immune to frequency shifts due to the presence of blackbody radiation (BBR). Using quantum-enabled spectroscopy techniques, the research team aims to develop an optical atomic clock based on narrow linewidth transitions in highly charged praseodymium ions (PrXI). A highly charged ion optical clock with a fractional systematic uncertainty at the level of one part in ten to the eighteen, when compared to an optical clock based on singly ionized ytterbium (YbII), could lead to a factor of one hundred improvement in the current laboratory limit on time-variation of alpha. Either an improved limit on the constancy of alpha, or a non-zero signal of the time-variation of alpha could be used to constrain physics beyond the standard model of particle physics. Results from this experimental work will be analyzed in the context of theoretical extensions to the standard model that propose new dark matter candidates and couplings that would lead to the observation of a non-zero value of the time-variation of alpha. 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

Per- and polyfluoroalkyl substances (PFAS) are a group of manmade chemicals that are used in many consumer products and industrial processes due to their unique chemical properties. However, their persistence in the environment poses a significant threat to the drinking water supply of roughly one in three people in the U.S. One promising method for PFAS removal from contaminated water is nanofiltration (NF), a technique that removes nanoscale particles from a liquid using membranes as a filter. Yet, several critical challenges must be addressed to make NF a viable part of PFAS cleanup efforts. First, the effectiveness of NF in removing the wide variety of PFAS types, especially (ultra)short-chain PFASs and those found in complex mixtures, remains unknown. Second, a better understanding of how various forms of PFAS interact with NF membranes at a molecular level is needed. Third, the lack of predictive models to identify key factors that affect PFAS passage through NF membranes hinders rational membrane design and selection. This research aims to address these knowledge gaps by combining experiments and computer simulations, integrated with specialized modeling techniques such as machine learning, to investigate how NF removes PFAS from contaminated water resources. The fundamental knowledge gained through this work will advance membrane-based technologies for remediating PFAS-contaminated water. In addition, this project will include public engagement and educational activities such as developing a new educational module, training students from underserved groups, and hosting outreach activities for PreK-12 students to increase PFAS scientific literacy and awareness. The overarching goal of this research is to use an innovative integration of experimental and computational studies to elucidate the performance and mechanisms of (ultra)short-chain PFAS removal by NF. To achieve this goal, the NF removal performance for (ultra)short-chain PFAS of varied structural features will be evaluated, and the structure-property-performance relationship of PFAS removal in NF treatment will be established using machine learning techniques. The investigators will use non-targeted chemical analyses to further assess the NF performance in removing diverse PFAS from complex aqueous film-forming foam-impacted water. The interactions and transport of PFAS at the water-membrane interface and within polyamide NF membranes will be probed theoretically using molecular dynamics simulations to gain mechanistic insights into the experimental results. The findings of this research will generate fundamental knowledge to inform rational design strategies for developing more effective NF membranes tailored to remediating PFAS-contaminated water. 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.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Wildfire activity is increasing resulting in greater numbers of firefighters conducting suppression and prescribed fire activities each year to protect lives and property. In conducting these activities, individuals are exposed to occupational factors that increase the risk of acute and chronic illness, including prolonged and elevated exposure to smoke particulate. Fine smoke particulate is known to penetrate the lung and has recently been associated with impacts outside the lung including in the reproductive system. In fact, our lab has demonstrated that laboratory generated wildfire smoke exposure at occupationally relevant levels alters sperm epigenetic patterns in a mouse model. The National Fire Service Research Agenda Report recently highlighted the potential for reproductive risk and stated that infertility issues that result from being a firefighter should be a priority research objective. In response, we have designed three aims to determine the extent to which wildland firefighter activities, particularly wildfire smoke inhalation, impacts fertility among male wildland firefighters. For Aim 1, among 100 wildland firefighters, we will assess cross-season paired samples for concentrations of motile sperm as a marker of fertility and in Aim 2 we will quantify epigenetic modifications in a subset of 50 wildland firefighters as a predictor of quality and offspring health. The outcome of Aims 1 and 2 will be the first characterization of adverse sperm parameters and molecular changes that occur in wildland firefighters following occupational exposure to smoke, which will inform early detection and intervention strategies for occupation-related infertility issues. For Aim 3, we will combine the findings from our study with other current literature to craft messaging material informing firefighter personnel about the potential adverse exposure impacts, as well as precautionary measures which may protect their reproductive health. We will seek feedback via wildland firefighter focus groups (n=20) on how to craft the message as well as what they view as trusted channels for dissemination. The outcome to Aim 3 will be a strategic communication plan that can be adopted and modified by the fire service to enhance the reproductive health and wellbeing of male wildland firefighters.