Florida State University

NSF Awards · FY 2025 · 2025-07

This project investigates how instabilities develop in fluids—whether in the air, oceans, or even within jet engines—by analyzing the Euler equations, which are the fundamental equations that govern fluid motion. The principal investigator (PI) studies new scenarios in which a steady fluid flow can suddenly become unstable due to small disturbances. This includes studying both linear instabilities, which approximately describes the early stages of disruption, and nonlinear instabilities, which govern a precise notion of a fluid flow and can lead to a justification of an eventual breakdown into turbulence. The PI focuses on degenerate cases which can be quite difficult, such as axisymmetric flows in three dimensions—flows that are symmetrical around an axis but may become unstable when slightly disturbed in a non-symmetric way. These cases can be especially complicated near the axis of symmetry and pose major mathematical challenges. Another aspect of the project is concerned with the behavior of irregular flows, such as those arising from vortex sheets, where sharp changes in velocity occur. By improving our theoretical understanding of these instabilities, the project promotes the progress of science, since better models of fluid instability help inform a wide range of applications, from improving the efficiency of transportation and energy systems to enhancing weather prediction. The project investigates the phenomenon of instabilities of solutions to the three-dimensional (3D) incompressible Euler equations, and develops a theory linking linear and nonlinear instability theorems with the local well-posedness and ill-posedness theory of the equations. The project investigates both the case of “local instabilities”, where new functional frameworks are developed to capture multiscale the behaviour, as well as the case of “global instabilies” in the form of neutral limiting modes, which can be treated as perturbations of an eigenvalue problems. As a central example of local instabilities in the 3D case, the PI considers vortex columns, and establishes connections between multiscale instabilities and the upper and lower neutral limiting modes of vortex columns. Another aspect of the project investigates nonlinear instability arising from irregular velocity fields, such as velocity fields arising from vortex sheets. The PI investigates two-dimensional steady states in the form of parallel shear flow, and establishes a rigorous relationship between instabilities of shear flows with a localized inflection point and Kelvin-Helmholtz instabilities of a flat vortex sheet, as well as a theory of nonlinear instability of logarithmic spiral vortex sheets, based on the bicharacteristic approach. 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 2025 · 2025-07

Red tides, a type of harmful algal bloom, are becoming increasingly common in waters along the U.S. Gulf Coast due to warming ocean waters. Red tides are caused by the rapid growth of a type of marine microorganism that thrives in warm coastal ocean waters and contains dangerous neurotoxins. As a result, these tides pose a threat to public health. Sea spray, from breaking waves or storms during red tides, kicks aerosols into the air, and these are carried by the wind over beaches and coastal communities. During red tides, there are reports of increased incidences of human respiratory conditions, like asthma and pneumonia, among others. This research focuses on improving red tide forecasting and assessing and mitigating public health impacts. It does this through an innovative model-data integration framework designed to improve the prediction of red tides and their link to human health. Research involves an interdisciplinary team of experts in modeling, marine ecology, data science, and medicine. Southwest Florida, a hotspot for red tides with a large coastal population, serves as a testbed for the research. It was chosen because it has abundant, relevant, and accessible data for both red tide occurrences and population respiratory health. This research fills a present gap in our understanding of the link between red tides and respiratory illness burdens. Broader impacts include results that can lead to a red tide early-warning system. It also helps support adaptive strategies that enhance the resilience of coastal communities and helps guide public health preparedness. The research trains students and postdoctoral researchers to work on the boundary between geoscience and health. The research serves the national interest through advancing the national health and welfare by promoting the progress of science to address a growing health concern in coastal communities. This project explores a new model-data framework that advances predictions of red tides and their tie to human health conditions under changing coastal water conditions in the U.S. Gulf Coast. Earth system modeling that incorporates oceanographic, atmospheric aerosol, and other geoscience data will be combined with the occurrence of health issues to discern dynamic relationships between red tides and human health. The research involves analysis of spatial and temporal data of both issues and is designed to fill the gaps between Earth System modeling results and health records. This involves integration of simulations from the High-Resolution Model Intercomparison Project (HighResMIP) with machine learning to develop a framework for combined red tide prediction and health risk assessment. It harmonizes red tide occurrence records, environmental observations (e.g., ocean temperature, Loop Current dynamics, wind speed and direction, river discharge, nutrients), and public health data from hospitals and clinics. Models trained on these data will identify links between red tide dynamics and respiratory health burdens. Research results include generation of a linked database of red tide and respiratory illness, scenarios that identify land–ocean–atmosphere drivers of red tides, and creation of risk metrics for public health mitigation including red tide severity and a respiratory impact indices. The project provides an open-science framework that advances the NSF mission of promoting the progress of science and advancing the national health and welfare. 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 2025 · 2025-07

This I-Corps project focuses on exploring the commercial potential of a photographic analysis method that determines chemical composition from patterns left behind by evaporated liquid drops. These stains, which form on common surfaces, contain structural features that reflect underlying chemical properties of the original solution. This solution could address the need for affordable, rapid, and user-friendly chemical testing, particularly in water quality analysis, where existing methods either lack precision or require costly instrumentation. Millions of households and businesses in the United States depend on water testing for health, environmental, or regulatory reasons, yet many do not have access to reliable and convenient options. This project aims to deliver a new solution that uses images captured by conventional smartphone cameras, enabling broad accessibility without the need for specialized training or laboratory resources. By lowering barriers to chemical analysis, the technology serves the national interest in promoting public health, environmental monitoring, and technological innovation. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of machine learning models trained on large libraries of stain images created by evaporating aqueous solutions with known compositions. The method extracts quantitative metrics from these images—such as texture, symmetry, edge complexity, and crystal morphology—and uses statistical learning to correlate them with chemical parameters like ionic strength, salt concentration, and water hardness. Unlike traditional assays, this approach requires no reagents, sensors, or chemical handling, and its accuracy improves with growing datasets and model refinement. If successful, the technology will offer a portable, cost-effective, and scalable platform for composition analysis, with future applications in fields such as beverage quality control, agricultural monitoring, and low-cost diagnostics. 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 2025 · 2025-06

When hot magma interacts with Earth’s crust, it changes the minerals and textures of pre-existing rocks by the process of metamorphism. Conditions of metamorphism depend on the pressure, temperature, and the kinds of fluids present in magmas and the crust. These processes can also change rock chemistry by driving the release of elements including carbon which may be liberated from the rock by decarbonation. The process of decarbonation is important in Earth’s long-term natural geochemical cycles. Decarbonation also produces residual rocks called skarns. Skarn deposits are often enriched in base (W, Cu, Pb, Zn) and precious (Ag, Au) metals; thus, a deep understanding of these processes promotes our understanding of economically valuable mineral deposits with broad societal value. Through their work on the project, students will be prepared for vital roles in the geoscience workforce. In particular, they will gain skills in quantitative research methods and numerical modeling to assess the tempo and mode of metamorphic processes that transport energy, fluids, and metals as magmas intrude and crystallize in Earth's crust. Given the close association with critical minerals, the work and student training opportunities constitute a front-line effort to sustain our understanding of resources that are important for the development and advancement of modern technology and the national security of the United States. On-the-ground public outreach efforts include engaging community members in primary and secondary school settings in Florida’s Leon County School District and the development of an exhibit of ore-minerals from the historic Mineral King District in Sequoia National Park. This exhibit will be housed in the Three Rivers Historical Society Museum, near the entrance to the National Park, where thousands of public visitors may potentially see it each year. This work focuses on high-pressure and high-temperature decarbonation of marble and calc-silicate rocks that have been exposed by erosion into the deep lower crust of the Sierra Nevada mountains, California. To understand the influence that metamorphic pressure, temperature, and fluid availability have on decarbonation and mineralization, the investigators combine tools from field work, laboratory study of mineral textures and chemistry, and numerical modeling. Field studies, both ongoing and planned, will focus on key skarn occurrences. Textural analyses by both polarizing and electron microscopes will help identify characteristic features in skarn minerals that formed during metamorphism. Geochemical measurements, including X-ray Fluorescence Spectrometry (XRF), Electron Probe Micro-Analysis (EPMA), and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM), will provide compositional insights at different scales—from whole-rock chemistry (XRF) down to micron-level details. Numerical modeling will further explore element and volatile migration in these lower crustal metamorphic settings, including carbon mobility and the geochemical processes controlling endowment of metals into ore deposits. 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 · 2025-06

Project Abstract Our long-term goal is to understand the genetic and molecular organization of circadian rhythms in mammalian models and humans, and the molecular mechanisms underpinning disorders of circadian rhythms and sleep. In doing so, we will provide important insights for treating a wide variety of diseases in which sleep disorders are major causes, symptoms, or comorbidities. We are pursuing three research areas under this common goal. 1) The genetic basis of human chronotypes and sleep disorders: Despite a clear causal link between genetic polymorphism in clock genes and sleep disorders, systematic investigation of pathogenic mutations in human clock genes has not been conducted for two reasons: The first is the abundance of natural genetic polymorphisms. There are thousands of known polymorphisms in major clock genes, a subset of which may affect chronotypes and sleep disorders. The second is the historical reliance on rodent models for functional assessment, which are time- and resource-intensive. To address this gap, we developed a cell-based in vivo- like platform that allows us to screen and characterize dozens of hypothesis-driven mutations along with natural human mutations in a cost- and labor-effective manner. Using our system, we identified novel mechanisms and mutations that can cause dramatically altered rhythms and sleep cycles. During the course of analyzing dozens of mutations in pacemaker clock genes, we found common themes that allow us to identify potential pathogenic mutations and predict their phenotypes. 2) The molecular link between the circadian clock and sleep homeostasis: Sleep is regulated by two distinct but interconnected mechanisms: sleep homeostasis and the circadian clock. Optimal sleep quality requires alignment of these two sleep-regulating pathways, and disruptions in either one can lead to sleep disorders. However, the mechanistic links between the circadian clock and sleep homeostasis have been largely unexplored. Recently, we serendipitously found that a Per2-driven clock in Per1 knockout (KO) mice behaves very differently from a wild-type (wt) clock and from a Per1-driven clock in Per2 KO mice when they are perturbed by long light pulses. Per1 KO mice showed dramatic phase shifting, called type 0 resetting, while wt and Per2 KO mice exhibited weak (type 1) resetting. Per1 KO mice always reset to CT12, the time of activity onset or lowest sleep pressure, regardless of when the light pulses were given. The Per2-driven oscillator seems to measure or regulate temporal sleep pressure, in addition to driving circadian rhythms. We propose to continue this line of investigation to unravel the molecular link between the clock and sleep homeostasis. 3) Identification of novel clock genes: We engineered a human cell line with a functioning circadian clock (U2OS) to express fluorescent protein-fused clock proteins from endogenous loci and thus report expression of endogenous clock genes. With powerful CRISPR lentiviral libraries targeting all human genes, we will identify novel candidate genes that affect expression of the reporter clock genes by FACS and high-throughput sequencing.

NSF Awards · FY 2025 · 2025-06

This award supports research aimed at enhancing our understanding of human motor learning to improve health outcomes. The project focuses on developing movement-assistive robotic technologies to aid in human motor learning and rehabilitation, especially for complex whole-body tasks like walking. The objective is to explore how humans learn intricate balance tasks and how robotic devices can facilitate that learning process. This research looks to contribute to foundational knowledge that scientists and engineers rely on to create robotic devices capable of transforming movement rehabilitation, improving learning outcomes, and advancing our understanding of human-robot interaction. Movement-assistive robotic technologies, such as lower-limb exoskeletons, hold substantial promise for enhancing human motor learning and rehabilitation, particularly in situations where there is a perceived risk of falling. The mathematical complexities involved in modeling the complex dynamics of human movement, like walking, have hindered research into how assistive devices can aid human motor learning. This project aims to simplify the study of balance and forward propulsion by using a single-wheel vehicle model. The foundational knowledge gained looks to help determine how to apply robotic assistance to more common balance tasks, such as walking. Additionally, the study will explore the development of adaptive robotic controllers that can accelerate skill acquisition. While there has been some exploration of human motor learning for simple, two-dimensional tasks like point-to-point reaching, much less is understood about how people learn three-dimensional tasks with a high risk of falling, such as walking. Furthermore, there is limited knowledge on how robotic assistive devices should intervene to facilitate accelerated motor learning. The team will simulate paired "student" and "coach" robotic learning agents, where the student learns while the coach guides the learning process. Finally, they look to develop a robotic assistance testbed and apply insights from experiments on human learning and robot simulations to evaluate the impact of human physiological and cognitive reactions, such as fear of falling, on the mechanics of learning. The team will also test how various assistive controllers aid human balance learning. 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 2025 · 2025-04

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Kristina Hakansson and her group at the University of Michigan are working to improve our ability to characterize the chemical structure of molecules, including especially biomolecules such as proteins, nucleic acids, and carbohydrates. Such structural analysis is essential to help us understand the function (and malfunction) of molecules in complex samples, e.g., biofluids, cells, and tissues. It is also crucial for the safety of therapeutic biomolecules. The Hakansson laboratory employs electron irradiation of gaseous, charged biomolecules to yield diagnostic fragmentation. Depending on their energy, electrons can either be attached or cause detachment of electrons from both cationic and anionic molecules. While electron attachment to cations, resulting in electron capture dissociation (ECD), and electron detachment from anions,resulting in electron detachment dissociation (EDD), are energetically favorable and structurally informative processes that have been relatively broadly applied, including commercial implementations, many questions remain about the underlying mechanisms as well as how these processes can be tuned and how the resulting data should be interpreted. Electron attachment to anions and electron detachment from cations are less favorable processes; however, the Hakansson laboratory has shown in previous work that negative ion electron capture dissociation; niECD is feasible and shows unique advantages for structural analysis of acidic biomolecules such as phosphorylated and sulfated analytes. Recent work from the Hakansson group has also shown that electron detachment from cations (tandem ionization) can occur at much lower electron energies than previously demonstrated. This research is providing new approaches to biomolecular structural characterization with important implications for drug discovery and enhanced understanding of the molecular basis of living organisms. Students working on these projects gain exposure to highly interdisciplinary research. Dr. Hakansson and her group also works to bring appreciation for these concepts and for broader science opportunities to middle school students in an effort to boost interest in the scientific method at an early educational stage. Under this award, the Hakansson group will explore electron energy vs. flux effects in positive and negative ion mode on both upgraded Fourier transform ion cyclotron resonance (FT-ICR) and beam-type implementations. This research seeks to elucidate whether “hot” ECD is not an energy but an electron density effect, tentatively termed electron flux dissociation; EFD. Resulting spectra are rich in structural information, including amino acid side chain cleavages that can differentiate isomers and carbohydrate cross-ring fragments that provide linkage information for branched analytes. Similarly, recent reports of internal fragments resulting from two backbone bond cleavages in proteins following electron irradiation do not appear to be a result of “true” ECD but rather an electron flux effect. In addition, because internal fragments have many isomeric and isobaric assignment possibilities, false discovery rates are high. The Hakansson group seeks to elucidate all fragmentation pathways leading to terminal fragments, including hydrogen shuffling, radical a-type ion formation, and accompanying water/ammonia losses that can be erroneously assigned to internal fragments. In addition, they will explore the role of de-isotoping errors in such assignments. Furthermore, they will contrast EDD, which shows only two main fragment ion types, to collisional activation, which shows up to eight fragment ion types, with regard to false discovery of terminal and internal fragments from oligonucleotides. Finally, the Hakansson team will leverage these insights with an eye toward improved alignment of ion-electron reactions with liquid chromatography-tandem mass spectrometry analyses of labile post-translational modifications and oligonucleotides. 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 · 2025-03

PROJECT SUMMARY Tuberculosis (TB) has inflicted a quarter of the worldwide population and caused 1.6 million deaths in 2021 alone. However, there have been no new classes of TB drugs developed since the 1970s. New therapies are desperately needed as multi-drug and extensive drug-resistant TB cases have increased rapidly. The primary reason for drug resistance is latency, where the causative agent, Mycobacterium tuberculosis (Mtb), remains non-proliferative in the patient’s body. Understanding the cell division process in Mtb through structural characterizations of the participating protein complexes is critical for designing resistance-breaking therapeutics and is the objective of this project. Bacterial cell division is mediated by the divisome, which comprises dozens of proteins spanning the cytoplasmic membrane and the periplasm, with the Z-ring as the scaffold. We recently discovered that the cytoplasmic N-terminal region of Mtb FtsQ binds FtsZ, which is the protomer of the Z-ring, and hypothesized that FtsQ may stabilize the curvature of the Z-ring and anchor the Z-ring to the inner membrane. In E. coli, FtsQ forms a ternary complex with FtsB and FtsL to activate enzymes that are responsible for the synthesis of cell walls. However, the amino-acid sequences of the Mtb FtsQ, FtsB, and FtsL are distinct from their E. coli analogs, suggesting different structures and functional mechanisms. The Specific Aims of this project are: (1) to investigate the structural and functional roles of the FtsQ-FtsZ interaction; (2) to characterize the structure, interaction, and function of the FtsQ-FtsB-FtsL complex; and (3) to develop 17O NMR for probing membrane protein interactions. This work will employ advanced solid-state and solution NMR combined with molecular dynamics simulations to characterize protein complexes in native-like membrane environments. The proposed functional studies will establish crucial connections between structural insights and biological activities, with profound implications for drug resistance. Our interdisciplinary team, with expertise in NMR spectroscopy, computational biophysics, and microbiology, is ideally positioned to accomplish the proposed studies. This research will yield critical knowledge on the cell division process in Mtb and help identify drug targets for effective therapeutic strategies to address the TB epidemic. The new methodologies that we will develop represent the frontier of protein structural biology.

NSF Awards · FY 2025 · 2025-03

This Computational and Data-Enabled Science and Engineering (CDS&E) collaborative research project will contribute to the progress of science and the advancement of national prosperity by developing a framework for the inverse design and fabrication of multiphase composite materials with tailored mechanical properties. Despite recent advances in the deployment of machine learning techniques to materials science, the creation of materials with desired mechanical properties in multiple loading directions remains a significant challenge. This research plans a new data-driven framework to understand the relationship between material architecture and mechanical behavior, facilitating the design of nonlinear materials for a wide range of applications such as lightweight structures, shock absorbers, and aerospace components. This research will be integrated with educational and outreach programs aimed at attracting underrepresented groups to engineering and improving undergraduate and graduate learning in data-driven science and engineering. High school students and the public will be introduced to data-driven material design and applications in collaboration with a local museum and science center. This collaborative research will create and test a new physics-informed deep learning (PIDL) framework to tailor the multidirectional or multi-objective mechanical properties of exotic composite materials. It will utilize the principles of PIDL to build a data-efficient and physically interpretable surrogate model of structure-property relationships for multiphase composite materials. This research will formulate constitutive equations for constituents in voxel-based composite materials and incorporate them into a forward physics-informed convolutional neural network model. A novel multi-objective inverse physics-informed conditional diffusion model will be developed to reveal the property-structure correlation between a multiphase composite material’s bulk mechanical properties and its architecture, combining macroscopic and microscopic data to enhance model accuracy and robustness. Finally, the designed materials will be additively manufactured and tested, with validation through advanced additive manufacturing, X-ray imaging, and multiaxial testing. 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 2025 · 2025-02

This project tracks citizens’ attitudes toward a judicial reform effort and the judiciary as these reforms are implemented, as citizens elect their judges, and as the directly elected judges are seated. The reforms call for the direct election of more than 7,000 of the most important judicial positions in the country. Because judicial independence is associated with salutary governmental and economic outcomes, and public support for judicial institutions is a key determinant of judicial independence and influence, this project has implications for understanding how the direct election of judges might bolster or undermine institutional separation of powers, economic development, and broader international relations. Most of the accumulated knowledge about the public's support for the judiciary has relied upon surveys asking citizens for their evaluations of hypothetical proposals to reform the country's high Court. The reforms that prompt this study provide an opportunity to test theories about the correlates and consequences of public support for courts in an environment where the stakes are real and cross-national comparisons are feasible. Tracking public opinion over a four-wave panel survey and analyzing unique survey experiments, this research will address three debates. First, each wave of the survey will reach respondents at a point in the reform implementation that enables researchers to disentangle longstanding theories regarding the determinants of public support for judicial institutions. Second, relying on within-respondent, cross-wave comparisons, the PIs will evaluate the extent to which the electoral connection affects citizens’ legal attitudes about courts and judicial authorities, and their willingness to engage them as a result. Third, the PIs will assess how the reform---and citizens' responses to it---affect their willingness to obey decisions they do not agree with and to tolerate noncompliance with constitutional authorities' decisions. These outcomes have direct relations to the country's ability to attract international investment and to ensure that the separation of powers balances power across the executive, legislative, and judicial branches of government. 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 2025 · 2025-01

This U.S.-French joint research project addresses the growing interest in modeling, analyzing, and generating 3D shapes and movements of human bodies and faces. Advances in scanning technology, 3D mesh-extraction algorithms, computer vision, and hardware-accelerated computer graphics have enabled access to large-scale datasets of human body representations. However, while artificial intelligence and machine learning have achieved remarkable success in processing image data, working with 3D shapes in the form of meshes presents unique challenges that often degrade performance in common computer vision and graphics tasks. To overcome these challenges, this project aims to integrate rigorous shape analysis concepts into the design of geometric deep learning models. These models will directly process raw 3D surface scans, independent of acquisition methods, to develop robust algorithmic pipelines for key problems in human body and face analysis. Applications of this work include single-object data representation and reconstruction, body motion generation, facial expression retrieval, and automatic animation. Beyond its implications for augmented and virtual reality, the project will train graduate students and strengthen collaboration between investigators from four institutions in the U.S. and France. The research focuses on developing efficient deep learning architectures that incorporate fundamental shape invariances into machine-learning pipelines. It consists of three key thrusts: (1) Invariant 3D-to-3D Registration and Reconstruction: This thrust will develop a framework adapted to human body shapes and face scans, combining mathematical shape analysis concepts with advancements in latent space and auto-encoder models in computer graphics; (2) Extension to Time-Dynamic (4D) Data: Building on static 3D data, this thrust will extend methods to dynamic 4D data (3D plus time) for motion analysis and generation. The approach will involve constructing a non-linear structure in the human shape latent space, using a blend of data-driven techniques and physically motivated elastic deformation energies. This will allow accurate modeling of the complex nature of real-life human body motions and deformations; and (3) Prompt-to-Shape Learning: This thrust will focus on mapping prompts, such as text or voice recordings, to shape spaces. Through these efforts, the project seeks to advance the state of geometric deep learning and its applications while fostering international collaboration and academic training. 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 2025 · 2025-01

Biological production in ocean surface waters is an important part of the global carbon cycle. In some areas, particularly high latitudes, the availability of iron – an important but scarce nutrient element – can limit the amount of production. It is important to understand sources of iron to the ocean in these regions. This project will focus on the role that ocean sediments play in supplying iron to the surface waters of the Labrador Sea, between Canada and Greenland. The team will collect sediments and sediment pore waters to identify and quantify iron sources from the sediments to overlying ocean waters. They will use numerical models of ocean circulation to study the possible transport pathways of this iron to surface waters where phytoplankton can use it. The project will support graduate and undergraduate students. The team will focus on effective mentoring with the goal of supporting young scientists who identify with groups historically marginalized in oceanography. This will be achieved through two linked approaches: 1) practical and inclusive training of two students who have never been to sea before, and 2) supporting a polar science mentoring network by funding an undergraduate coordinator for the Polar Impact Mentoring Initiative (PIMI). This project investigates benthic iron fluxes in the Labrador Sea, an important region of deep-water formation where the efficiency of the biological carbon pump may be influenced by iron availability. Glacial meltwater from the Greenland Ice Sheet provides iron to this region, but glacial iron is estimated to sustain less than half of the annual productivity, restricted to late summer blooms during peak meltwater discharge. Thus, additional iron sources from the sediments are likely important. The proposed research tests the hypothesis that continental shelf sediments provide iron (through reductive and nonreductive release) that can be transported in shelf currents to the surface water and the interior Labrador Sea. In conjunction with a previously-funded research expedition, pore water and solid sediments from multicore subcores will be sampled for iron speciation and isotopes, and unique, two-dimensional iron sensors will be deployed on deck along with a suite of other sensors (oxygen, pH, temperature). The 2-D iron sensors generate high-resolution iron(II) concentration profiles for accurate estimation of diffusive fluxes across the sediment-water interface. These datasets will reveal the biogeochemical conditions in the surface sediments and the magnitude and speciation of the resulting iron flux. Finally, the team will investigate possible transport routes from the continental shelf sediments to the euphotic zone in the Labrador Sea using a model of circulation in the region. These tracer experiments will reveal the potential physical fate of benthic iron in the system and test the feasibility of benthic iron fertilizing the surface ocean in the region. 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 2025 · 2025-01

The rapid evolution in the power grid is driven by sustainability concerns, with focus shifting significantly towards renewable energy sources and away from fossil fuels. Meanwhile, the rise of electric vehicles (EVs) has accelerated the electrification of transportation. Accordingly, this project proposes an interaction-aware management framework to improve the efficiency and sustainability of these two independent and self-interested systems. Since both the EV transportation system and the power-grid system are managed by distinct stakeholders and operate within different domains, they function independently and without coordination, impacting their overall efficiency and causing issues such as voltage instability, frequency fluctuations, high financial costs, and long charging durations. Past work has accumulated abundant knowledge on how to design each system independently; however, strategies to achieve synergistic outcomes beneficial to both parties remain under-explored. It is therefore crucial to develop a collaborative framework that considers how each system responds to the other's actions, such as how power grids adjust electricity prices based on EV charging demands and how EVs choose charging stations based on price and availability. This collaboration is expected to benefit both EV drivers and power-grid operators, reducing costs and improving sustainability. In terms of broader impact, the project also includes capacity-building, education, and outreach initiatives to promote the participation of underrepresented minorities in the modern EV-related workforce. Technically, the project will focus on the following three key components: (1) a robust multi-agent reinforcement-learning control model for power systems to dynamically adjust electricity prices and charging-power rates, which integrates a human charging-behavior model for enhanced accuracy and efficiency; (2) a mean-field game-based control method for large-scale EVs to autonomously select charging stations in a decentralized fashion with awareness of potential charging rates; and (3) an incentive-driven collaboration mechanism to facilitate socially optimal actions between the power grid and EV operators using graph-based multi-agent reinforcement learning and Shapley value. The project will use real-world data to validate its approach and ultimately contribute to the development of a more sustainable transportation and power infrastructure. 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 The consumption of food and beverages is highly dependent on the initial sensation and the response it evokes. This sensa- tion arises within the mouth and involves the integration of intra-oral gustatory, olfactory (retronasal), and somatosensory cues in a single percept called flavor. Research over the years has extensively evaluated the behavioral and physiological correlates of one of these intra-oral sensory components – taste – which originates when chemical compounds stimulate specialized chemoreceptors within the oral cavity. Most of what is known about the neural and perceptual substrates of taste originates from studies in which stimuli are experienced at a single temperature. While this approach has shaped our understanding of the role of gustation, it provides only a partial picture of the functional features of the gustatory system. In natural conditions, chemicals present in food and beverages are rarely experienced at a single-fixed temperature. Temperature is a salient cue that can influence the sensory attributes of food and the perceived intensity of taste qualities relevant for food and beverage preferences and nutrition. Thus, based on the serving temperature, we might alter the amount of certain ingredients to match our preference leading to over/under consumption of certain food elements. This is particularly relevant in the case of table salt (NaCl). This could result in a diet high in sodium which can cause serious health consequences such as high blood pressure, stroke, and other cardiovascular issues that can increase the risk of, or even cause, death. Therefore, the primary objective of this proposal is to explore the impact of temperature on salt taste perception and its neural processing in the cortex of behaving mice. The first aim involves a behavioral study to determine how temperature affects the ability to discriminate the taste quality of NaCl and KCl. The second aim will employ electrophysiological techniques to investigate the influence of temperature on the cortical representation of salt taste, particularly regarding its intensity and quality aspects. This research is designed to lay a foundational understanding of how thermal and taste stimuli, commonly encountered in food and beverages, are integrated. Altogether, the results obtained from this proposal will expand the current knowledge on thermogustation, and will provide a comprehensive behavioral and neural investigation on how temperature operates on sensory processes associated with taste.

NSF Awards · FY 2024 · 2024-12

The rapid spread of wildfires and associated smoke plumes undermines the health and safety of communities, the effectiveness of firefighting efforts, and complicates the evacuation of residents. This project aims to gain predictive understanding of the physical processes for rapid wildfire spreads. This will help to guide firefighters to more safely and effectively suppress fires with an improved adaptation to diverse surrounding atmospheric conditions. The predictive understanding of the environment conditions conductive to re-entry of smoke plumes back to the ground will help develop new tools and engage the community of practitioners to open the “window of prescription” for prescribed fire. This project will engage with national training center workshops to demonstrate the impact of fire-generated turbulent flows on surface smoke dispersion, spotting, and fire spread. Local and regional agencies will be exposed directly to new developments in wildland fire research through workshops and site visits. This project will train two Ph.D. students and a postdoc in fields of atmospheric dynamics, modeling, and data science. The research findings will be communicated to the science community via peer-reviewed publications and to college students via classroom teaching and curriculum development. The innovation of this project lies in the consolidation of common characteristics between two distinct phenomena—naturally occurring density currents and fire-generated warm plumes. This allows for a direct application of the physical understanding of observed large-scale turbulent flows in naturally occurring density currents to the rapid growth of billows in fire smoke plumes by considering additional physical factors that are unique to fire-generated plumes, such as non-hydrostatic conditions and thermal expansion. The central hypothesis of this research links rapid advancement of wildfires to the rapid non-modal growth of large-scale Kelvin-Helmholtz billows beneath fire-generated buoyant plumes. In concert with the continuous surface fire spread, spotting occurs as airborne burning embers enter large-scale billow-like turbulent eddies within smoke plumes. The rapid falling of airborne burning embers back to the ground ignite new fires at a considerable distance downstream from the existing fire front. Additionally, under conducive environmental conditions, successive large-scale billow-like turbulent eddies can cause elevated smoke concentration near the ground over considerable distances from the prescribed fire site. This project will perform non-modal instability analysis of fire smoke plumes to delineate the key processes responsible for rapid growth of billow-like large-scale turbulent flows under different environment conditions. The research team will utilize large-scale eddy simulations to validate the results of non-modal instability analysis and investigate their underlying dynamics and thermodynamic processes. 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

This project will assess the effect of floods and landslides caused by Hurricane Helene on spatial genetic and phenotypic variation of freshwater fish populations in the southern Appalachian Mountains. Extreme events provide a rare opportunity to investigate the role of disturbance on evolutionary processes. The record-breaking river flows and the transport and deposition of sediment associated with Hurricane Helene is likely to have profound impacts on freshwater fish. Flooding may influence population diversity by causing mortality, physically moving individual organisms across the landscape, or restructuring suitable habitat and dispersal pathways. The project will resample approximately 20 sites across the upper Tennessee River, the Savannah River, and the Santee River in western North Carolina and Tennessee that were previously sampled from 2021-2024, prior to Hurricane Helene. This research will contribute to the essential effort to understand how biodiversity will be affected by a changing planet. The research is of particular importance in the southern Appalachian Mountains, which is located within a temperate freshwater biodiversity hotspot and hosts an exceptional number of freshwater fish species. Results from the proposed work will be communicated to conservation practitioners at the annual Southeastern Fishes Council meeting. Evolution may be contingent on stochastic and impactful events like mutations or extreme abiotic disturbance, and it has been proposed that historical contingency can reduce the degree to which evolution is predictable. Alternatively, natural selection may determine the outcomes of stochastic events, yielding predictable evolutionary trajectories. We will rely on our pre-storm collections of genomic datasets or tissues, targeting seven species that vary in body size, reproductive strategies, and microhabitat preference: Nothonotus chlorobranchius (Greenfin Darter), Etheostoma blenniodes (Greenside Darter), Hypentelium nigricans (Northern Hogsucker), Luxilus coccogenis (Warpaint Shiner), Nocomis leptocephalus (Bluehead Chub), Notropis rubricoceus (Saffron Shiner), and Notropis spectrunculus (Mirror Shiner). The project will use doubledigest restriction site associated DNA sequencing to assess changes in spatial genetic variation before and after the storm, and compare morphological and meristic traits in pre- and post-storm specimens. The project will assess whether the effect on evolutionary processes can be predicted by the degree of abiotic disturbance by using geomorphic observations to estimate discharge and shear stress at maximum flood stage and will assess the influence of landslides and debris flows through analysis of remotely sensed topographic and satellite datasets. 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 unlicensed Industrial, Scientific, and Medical wireless frequency bands at 2.4GHz have supported a broader range of emerging Internet of Things (IoT) applications that benefit people’s daily life. Diverse wireless protocols supporting heterogeneous IoT devices coexist on the crowded 2.4GHz, resulting in a significant challenge of spectrum management. Their uncoordinated multiple access not only quickly depletes the limited spectrum resource but also significantly drains the power of low-complexity IoT devices. This project designs a novel hardware-software co-design communication framework that enable parallel communication for heterogeneous IoT devices, fundamentally enhancing spectrum utilization and power efficiency. The proposed framework advances the understandings of enhancing the spectrum utilization and power efficiency for large-scale heterogeneous IoT systems, such as smart healthcare, industrial IoT, and many more crucial sectors requiring continuous connections among disparate system objects. The success of this project allows coexisting IoT devices to work coherently without compromising their own communication performance, which is indispensable for the wide adoption of heterogeneous IoT devices. By leveraging Software-Defined Radios (SDRs) as gateways to manage the IoT device, this project renovates both hardware and software stacks to enable future spectrum-efficient and power-efficient heterogeneous IoT systems. To minimize the power consumption in digital domain, Thrust 1 designs and implements a novel RF real-time signal processor for synchronizing SDR with heterogeneous IoT devices. Thrust 2 designs a new physical-level parallel inclusive communication paradigm for spectrum-efficient downlink transmission, by which a software-designed signal can be decoded by multiple protocols with exclusive messages. Combining the previous hardware-software efforts, Thrust 3 tackles uncoordinated multiple access by innovating a data-driven cross-layer approach for uplink transmissions among heterogeneous IoT devices. To ensure the framework's effectiveness, the team will build a testbed and collect data for public use. This project seeks to broaden the scientific view of undergraduates and underrepresented students in the minority-serving institution, Florida Agricultural and Mechanical University, in the field of wireless communications and networking and prepare them with the cross-disciplinary skills needed to succeed in the modern workforce. The integrated research activities proposed in this project will enhance the long-term collaboration among Florida Agricultural and Mechanical University, Clemson University, and Florida State University. 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

How does culture shape and compel human behaviors, and what are the health consequences of adherence or deviance with socially prescribed norms? This research project investigates the motivations for adhering to, or deviating from, cultural norms and the well-being outcomes of these behaviors. Research shows that conforming to group expectations, and the norms and values of one’s culture, facilitates the construction of social networks, acceptance, and well-being. Conversely, being deviant from shared cultural values is often stressful due to negative social feedback and lack of a sense of belonging. Yet, individuals within groups are not homogenous. Rather their behaviors are shaped by internal (e.g., personal beliefs) and external (e.g., social pressures) motivational forces, and limited by structural constraints (e.g., socioeconomic status). This research involves an international collaboration of anthropologists, psychologists, and biologists, and the training of graduate students, in ethnographic and biomarker data collection and analysis. It disseminates its findings broadly to academic and non-academic audiences. This research utilizes ethnographic and cognitive anthropological methods to evaluate ways by which culture values are shared, internalized, and enacted into behavior. Investigators employ cultural consensus and cultural consonance, and related approaches to identify shared cultural norms and individuals’ adherence to versus separation from such values. Health outcomes, particularly those associated with psychosocial stress, are measured through mental health surveys, as well as biomarkers such as blood pressure, and hair cortisol concentrations. This combination of health outcomes provides both acute and chronic measurements of psychosocial stress. A longitudinal research design evaluates changes in cultural behaviors and health and provides insight to potential causal associations. In doing so, this study furthers a biocultural understanding of how culture shapes health. 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 · 2024-09

Project Summary As the largest cortical recipient of direct olfactory bulb (OB) projections and a prominent part of the rodent brain, the piriform cortex (PCx) is considered to be a central hub for the processing and coding of olfactory information. While landmark studies have made significant progress towards deciphering PCx odor coding, there remains (in many cases) a significant disconnect between our understanding of olfactory perception and the coding principles that underlie it. For example, the PCx exhibits a massive over-representation of identity information that appears disproportional to the number of glomerular inputs necessary to encode odor features or drive odor-guided behavior. The efficient coding hypothesis predicts that in a low-noise situation (i.e., one with sparse receptor activation), the neuronal population should remove redundancies in order to most efficiently encode the stimulus. In a high noise situation (i.e., one with significant non-target receptor activation), the system should attempt to encode the stimulus in the most robust manner possible, by becoming highly redundant. Thus far, the stimulus concentrations utilized to examine PCx neural activity are typically many orders of magnitude above natural odorant concentrations - potentially signifying that these coding principles have been examined primarily in high neural noise situations. The ability to examine PCx neural activity within sparse receptor activation regimes will ultimately require knowledge about the limits of perceptual sensitivity and necessitate analyzing odor-evoked responses at both single neuron and ensemble levels. Here, we propose a technically innovative approach that will refine the current model of PCx odor coding. Specific Aim 1 will examine how the neural dynamics of individual and ensemble PCx neurons encode odor identity across different concentration regimes by utilizing high density recording across eight PCx locations, spanning a total A-P distance of 2.7mm. Specific Aim 2 will utilize the same electrophysiological approach in conjunction with our robust behavioral measures of sensitivity to investigate how the coding principles identified in Aim 1 predict perceptual ability. Achieving these aims will offer a unique and unparalleled window into odor processing by analyzing PCx neural activity at both local and mesoscale levels, across different concentration regimes, in a manner that can be correlated to perception.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Alcohol is a well-known myotoxin that with sustained use can culminate in alcohol-associated muscle disease (AAMD), characterized by muscle weakness and functional decline, along with metabolic impairments and decreases in muscle size (i.e., mass), that culminate in reduced quality of life. While mechanisms regulating protein balance have previously been implicated in AAMD development, additional pathways require exploration to develop new therapeutic targets as none currently exist. Our previous work indicates that both binge and chronic alcohol intoxication disrupt the core molecular clock within the skeletal muscle however, whether clock disruption contributes to the etiology of AAMD remains unknown. Overall, the long-term goal is to mechanistically determine whether alcohol’s influence on the skeletal muscle core clock impacts alcohol- associated disease risk, as well as to determine how alcohol modulates the core clock so that targeting of specific clock components can be used as therapeutic interventions. Specifically, skeletal muscle contractile strength is reduced by chronic alcohol use in a manner that closely parallels that caused by skeletal muscle- specific core molecular clock disruption (in the absence of alcohol), inferring that alcohol-induced disruption in the core clock may be responsible for AAMD associated weakness. Therefore, Specific Aim 1 of the current proposal is to determine whether disruption to the skeletal muscle core molecular clock contributes to the decreases in contractile function caused by chronic alcohol use. The second Aim will be to determine how alcohol consumption causes skeletal muscle core clock disruption so that preventative interventions can be developed. Specific Aim 1 will use a mouse model of muscle-specific circadian pathway dysfunction caused by the inducible deletion of the core clock gene Brain muscle arnt like-1 (Bmal1) to determine the role of the skeletal muscle clock on contractile function during alcohol intoxication. Specific Aim 2 will define the role of alcohol and alcohol-related factors in the disruption of the skeletal muscle clock by investigating the influence of both peripheral circulating factors produced during alcohol metabolism and the role of the central (i.e. brain- specific) administration of alcohol on the circadian function within the skeletal muscle. These research questions will be addressed by using a variety of physiological models paired with in vitro, in vivo and in situ techniques. This investigation will be the first of its kind in the study of the effects of alcohol on core clock function in the muscle and one of the few to consider the influence of peripheral tissues in the development of AAMD. Lastly, it will lay the foundation for continued mechanistic investigations to determine the role of the core molecular clock in AAMD.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Medical marijuana is legal in 37 states and the District of Columbia, and use among adults 50 and older has more than doubled in the past decade, with exponential increases projected by 2050. Adults 50 and older are among the largest consumers of medical marijuana, with chronic pain as their most frequently endorsed reason for use. In addition, the use of prescription opioids, one of the most common treatments for pain management in this population, is a factor complicating chronic pain management as those 50 and older are three times more likely to be prescribed opioids than younger adults. The primary goal of the current proposal is to identify the effects of daily long-term (i.e., use >12 months daily or most days of the week) medical marijuana use on driving performance outcomes using an open road test under real world conditions in adults 50 and older who endorse chronic or severe non-malignant pain; and examine the combined effect of daily long-term medical marijuana use and prescription opioid use on driving outcomes. A secondary goal is to qualitatively explore self-regulation of medical marijuana and prescription opioid use in this population. These goals are of the utmost significance given that THC is associated with a 50% increased risk for traffic crash, and the risk of motor vehicle collision while driving under the influence of marijuana is two times higher than when driving unimpaired. Further, opioid use is associated with a 47% increased risk of crash initiation and aging itself is associated with increased crash risk and declines in driving performance. Thus, the proposed study will test medical marijuana use as the exposure variable in adults age 50 and older and an open-road driving task performance as the primary outcome. The study will detail THC exposure through electronic medical records, urinalysis, and data extracted from RYAH Smart Inhaler devices, in conjunction with measures of open-road driving task. Further, we will use a race-sex matched group of non-marijuana users, and age variability will be balanced in both groups. Results will provide evidence for the effects of medical marijuana use and opioid positivity on a real-world driving task among adults 50 and older. To accomplish this, we propose the following aims: Aim 1: Identify the effects of daily long-term medical marijuana use on driving performance using an open-road driving task in adults 50 and older. Aim 2: Examine the combined effect of medical marijuana use and prescribed opioid use on driving outcomes via an open road driving performance task. Exploratory Aim: Identify intervention targets to improve self-regulation of medical marijuana use, prescribed opioid use, and driving performance in adults 50 and older. Given the proliferation of medical marijuana use and prescription opioid use in adults 50 and older, it is imperative that we understand the long-term effects of daily medical marijuana use and how co-occurring use with prescription opioids affects real-world driving outcomes. With our interdisciplinary team’s expertise and our current research infrastructure throughout the state of Florida, including our research partners, we are uniquely poised to execute this relevant and timely work.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY We propose to develop a new technology pathway towards 1.5 GHz 1H NMR, by building a 28.2 T (1.2 GHz 1H)/1ppm, all-superconducting NMR demonstrator magnet using coils of the High-Temperature Superconductors (HTS) Bi-2212 (Bi2Sr2CaCu2Ox) and Bi-2223 ((Bi,Pb)2Sr2Ca2Cu3Ox) nested inside an existing wide-bore, 12 T Low-Temperature Superconductor (LTS) magnet. The novelty of our proposal is that the primary HTS conductor technology will be Bi-2212, made using a process we have developed with DOE High Energy Physics support. In contrast to existing commercial HTS NMR magnet technology that is reliant on REBCO (REBa2Cu3O7-δ) tape conductor, Bi-2212 is a round, genuinely multifilament and isotropic conductor that does not suffer from the very large screening current induced stresses and error fields of the large width, single filament REBCO coated tape conductors. It is also presently made in 3-4 times longer lengths than REBCO, making it more appropriate for our long-term goal of creating magnets for 1.5 GHz 1H/ 35.3 T NMR spectroscopy, where 40-60% of the field must be provided by the HTS insert magnets. To make our proposal compatible with R01 funding possibilities, we pair two inner Bi-2212 coils with a larger diameter Bi-2223 coil as the HTS insert magnet. This strategy has two advantages: (i) we have more than 2 km of Bi-2223 and more than 3 km of Bi-2212 conductor available at no added cost to this project; and (ii) we can use the two HTS conductors to generate almost 60% of the total field as would be needed for going to 1.5 GHz magnets. The following capabilities available at the National High Magnetic Field Laboratory (NHMFL) enable the proposal: (a) A 212 mm bore, high-homogeneity LTS magnet supported by the Oxford Instruments (OI) team that built it; (b) a unique over-pressure heat treatment furnace (OPHT) facility for reaction of the Bi-2212 coils at the scale needed for NMR magnets; and (c) the essential expertise of NHMFL scientists and engineers with experience building high field magnets and magnetic resonance equipment for biological and biomedical applications. Successful demonstration of ultra-high-field NMR technology will meet the aggressive challenge of 1.3-1.5 GHz NMR articulated by the 2013 National Academy Panel assessing U.S. high magnetic field needs.

NIH Research Projects · FY 2024 · 2024-09

Project Summary/Abstract Erectile dysfunction (ED) is a progressive disease, which is often characterized by rampant fibrosis of the corpus cavernosum in severe disease states. It is hypothesized that hypoxia resulting from inadequate blood perfusion and/or depressed oxygenation is a primary driver of the fibrotic process in the corpus cavernosum. Moreover, ischemic priapism is highly prevalent in men with sickle cell disease. In these instances, sickling of the erythrocytes obstructs venous outflow from the corporal bodies, resulting in prolonged erections with minimal inflow of new blood into the penis. This stagnation of blood in the penis results in severe penile hypoxia despite the presence of a prolonged erection, which ultimately leads to advanced erectile function. This proposal is in response to PAR-23-119 “Catalytic Tool and Technology Development in Kidney, Urologic, and Hematologic Diseases”. Our goal is to develop a wearable device for prolonged penile oxygen saturation monitoring that can contour to the skin of the penile shaft, that is also flexible to movement and stretchable for expansion during erection. This proposal leverages our team’s recent innovation of a stretchable optical sensor photodiode for wearable photoplethysmography. We seek to optimize and validate this technology in rodents before advancing to testing in human patients. There are two specific aims to this proposal. Aim 1 is to design and fabricate optical sensors for rodent penile hemodynamic monitoring. Aim 2 is to determine if changes in measured oxygen saturation correspond with changes in rodent intracavernous pressure upon erection induction. Multiple variables can influence the oxygen saturation signal attained from photoplethysmography, as well as the depth within the tissue that the signal is obtained from. Major variables include the composition of the tissue through which light must penetrate, the wavelength of light emitted from the light source, and the light intensity emitted from the source. For this project, we will use both mice and rats due to the difference in thickness of the penile fascia, tunica albuginea, and cavernous smooth muscle and collagen through which light must penetrate and reflect off of oxygenated hemoglobin in the sinusoids. Devices will be fabricated to form fit the mouse and rat penile shaft, with three prototypes for each that contain micro light emitting diodes that emit different wavelengths of light. Three different light intensities will be used while testing each wavelength. Variable changes in intracavernous pressure will be induced by stimulation of the cavernous nerve with variable voltages. Additionally, both rapid and prolonged erections will be induced by intracavernous injection of sodium nitroprusside and papaverine.

NIH Research Projects · FY 2024 · 2024-09

Project Summary Up to 3 billion people will reside outside of the human climate niche due to climate change by the end of the century and the wholesale abandonment of communities are now a reality. As some communities in the US become increasingly environmentally precarious and settlements become abandoned, migration away from these areas could increase exposure to displacement-related stressful life events (DR-SLEs) and their impact on health. Such DR-SLEs are associated with short-term reduced health outcomes but little is known about how these short-term reduced health outcomes could translate into long-term reduced health outcomes. No database of US abandoned settlements currently exists, hindering our ability to study the long-term health impacts of DR-SLEs. This project will build a comprehensive database of all enumerated places since 1890 and verify any settlements abandoned during since. We will then leverage this database by linking verified, abandoned places between Census 1940 and 1950 to individuals in CenSoc, an NIA-funded database which matches deceased persons in the Social Security Administration’s Death File to their 1940 Census record, to estimate the causal effect of settlement abandonment on longevity using a synthetic control design. Findings from this project will directly inform ongoing federal, state, and local policies of managed retreat and illustrate the mortality penalty settlement abandonment could place on the millions of anticipated US-based climate migrants this century.

NSF Awards · FY 2024 · 2024-09

Despite comprising the largest racial/minority group in the U.S., Latiné students are marginalized in STEM, and are especially structurally disadvantaged in pathways to computing degrees. Despite the growth of the Latiné population, institutional leaders often lack access to effective strategies for authentically serving this growing demographic's needs for recruitment, retention, engagement, and advancement. This BPC Demonstration project at Florida State University will integrate evidence-based servingness criteria, effective transition strategies, tools, and methods to transform how the nation's 401 emerging Hispanic Serving Institutions (HIS) actively engage in their HSI transitions. As a result, this study aims to deepen Latinos' sense of belongingness on their campuses. The dissemination efforts will (1) leverage accessible formats and authentic Hispanic marketing to share insights on (how servingness is experienced at Hispanic Serving Institutions and (2) how emerging HSIs can establish context-specific benchmarking and implement associated strategies to best serve the Latiné STEM and computing communities. This demonstration project is a collaboration led by Florida State University (FSU), an emerging Hispanic Serving Institution (eHSI), and in partnership with fellow eHSI University of South Florida, University of North Carolina at Charlotte, and Excelencia Seal HSIs such as University of Texas at El Paso, University of Central Florida, and Florida International University, with the advice of BPC Centers including the Computing Alliance of Hispanic-Serving Institutions (CAHSI) and STARS Computing Alliance and experts from the Center for Hispanic Marketing Communication (CHMC). Using a mixed method multiple case study approach with a focus on Computer and Information Science and Engineering (CISE) majors, the team will conduct secondary data analysis and applied ethnography of HSI and eHSI, grounded in theories of authenticity and servingness, to accomplish four goals: 1) improved eHSI servingness to Latinos by documenting HSI's effective policies, processes, and practices eHSI's identified challenges to employing these strategies across organizational units (e.g., Student Affairs, Office of Research, Faculty Affairs, Admissions, Human Resources); 2) enhanced predominantly White institution (PWI) preparedness to serve Latinos using rigorous Seal of Excelencia requirements for data gathering and demonstration of the review process; 3) eHSI empowered to better serve Latinos with an HSI (R)evolution assessment rubric and toolkit; and 4) eHSIs supported in their transitions by disseminating project findings through traditional, bilingual, and multicultural multimedia academic channels. By using a multiple case study approach with a testbed eHSI PWI, this novel study will develop critical subject-matter knowledge on higher education institutions' evolution from eHSI to HSI. 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.