Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1383&sort=-award_amount
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MVTS instances represent states of dynamical systems and natural events using multiple time series of interdependent variables. Functional networks leverage the interactions of MVTS variables by finding higher-order relationships among them. The appropriate choice of data representation (MVTS or functional network) poses a challenge in machine learning (ML) efforts that can affect the performance of downstream tasks such as classification, regression, and clustering. This project will develop cyberinfrastructure that is public, web-based, and Graphical User Interface (GUI)-enabled and enables both novel and previously developed predictive, exploratory, and generative tasks on both data representations. The project serves the national interest by promoting the progress of solar physics science through facilitating solar flare prediction from MVTS-based solar magnetic field data and advancing national health through improving prediction models for neurological diseases (e.g., Schizophrenia) from fMRI-based functional brain networks. The research outcomes, including the cyberinfrastructure developed and ML models designed, will provide an opportunity for interdisciplinary research involving undergraduate students including those from underrepresented groups, for course curriculum development, and for high school outreach activities. MVTS instances are formed from the time series records of multiple sensors. In functional networks, the nodes represent the variables, and the edges represent the statistical similarity of the time series of the corresponding nodes. While in the MVTS representation completeness of data is preserved, noisy or missing data in time series due to events such as faults in sensors can compromise the performance of downstream ML tasks. Functional network representations help leverage multi-hop relationships of the variables, but the threshold-dependent sparsity in network construction can make ML models lose important features. Machine learning challenges of MVTS and functional network datasets include the appropriate choice of data representation and the limited number of training samples (especially in the medical domain). This project will provide a unified framework for performing (un)-supervised ML tasks on both data representations through application and customization of contemporary ML modes such as matrix/tensor decomposition, sequence models, Graph Neural Networks (GNN), and dynamic graph embedding. The project will also provide a framework for augmenting datasets with synthetic training samples through autoregressive, autoencoder-based, and adversarial models. The project will design and implement a web-based system that contains modules for data import and preparation, representation learning, data augmentation, validation, result visualization, and for exporting derived and synthetic datasets. The web platform will be hosted in the public domain, and its GUI-based front end will enable researchers to apply back-end ML models without explicitly programming using ML libraries.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12611", "attributes": { "award_id": "2306364", "title": "Collaborative Proposal: MSB-FRA: A macrosystems ecology framework for continental-scale prediction and understanding of lakes", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "MacroSysBIO & NEON-Enabled Sci" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28532, "first_name": "Erin", "last_name": "Schliep", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 245, "ror": "https://ror.org/04tj63d06", "name": "North Carolina State University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "Lakes are recognized as hotspots for processing carbon, nitrogen, and phosphorus and thus are critical for understanding how human activities affect global cycles of these essential nutrients. However, to estimate the total contribution of lakes in the United States to these global cycles, they have to rely on measurements from a small number of well-studied lakes because scientists do not have the resources to study every lake all the time. The resulting extrapolations to estimate global cycles and predict future change have many uncertainties. Consequently, it is important to understand where and when information from small subsets of lakes can be accurately applied to the wide variety of lake types and landscape settings across the continental United States. To improve future extrapolation efforts and to understand the role of lakes in global nutrient cycles, this award will build an unprecedented database that combines nutrient measurements from existing government and university monitoring programs (for about 15,000 lakes) with lake and landscape characteristics from national publicly-available digital maps for all lakes in the continental United States (about 130,000 lakes). Using this novel and unprecedented database, three components will be studied that are needed to determine the contribution of lakes to continental nutrient cycles. First, lake nutrients will be studied jointly rather than individually to provide insights into the conditions in which cycles are linked or not, which will help to reduce uncertainty in continental estimates of lake nutrients. Second, as scientists expand their studies from a few lakes to the entire continent, the relationships between lake nutrients and their landscape controls can differ in strength and even direction among different regions, further contributing to uncertainties in continental understanding of lake nutrient cycles. Finally, compiling data on every lake increases the chance of discovering novel environmental conditions that have not previously been studied, yet may play important roles in continental-scale nutrient cycles. Through these important research activities, scientists will increase their confidence in estimating the effects of lakes on global cycles. This award contributes to the broader scientific community because the database will be made publicly-available in a timely manner to complement the National Ecological Observatory program and to developing open-source advanced computer tools for analyzing large datasets for this and other big-data studies. In addition, the diverse team (by gender, career-level, and discipline) will train and mentor early-career scientists in interdisciplinary, team-based, and data-intensive science to be leaders in addressing challenging questions such as how future land use intensification and changes in global climate will affect lakes and the services they provide. Ecosystems, such as lakes, are complex, heterogeneous, and strongly influenced by their ecological context?environmental or anthropogenic factors that operate at multiple scales. This complexity makes extrapolating site-level estimates of ecological services, state, and function challenging. The overarching goal of this research is to understand and predict patterns in the three major nutrients for all continental US lakes to inform estimates of lake contributions to continental and global cycles of nitrogen, phosphorus, and carbon. The proposed work will address three important phenomena that limit scientists? ability to extrapolate freshwater nutrients at continental scales. (1) Because cycles of nitrogen, phosphorus, and carbon in inland water interact with each other and are often affected by similar controls, they should be considered as linked, not isolated. (2) As studies expand to view the whole continent, interactions between driver variables at different scales (cross-scale interactions) also increase. (3) A hallmark of the Anthropocene is the rise of novelty in ecosystems--new environmental conditions or new combinations of conditions. Such novelty may confound extrapolation in unknown ways. The proposed research is an unprecedented effort that will: address these important phenomena, develop new continental-scale data products for aquatic macrosystems ecology, and contribute novel, data-intensive analytical methods from computer science and statistics. This award will answer five research questions related to the above phenomena using two approaches. First, funds will be used to build a large, integrated database of all lakes in the continental United States (called LAGOS-US) that includes measures of in situ nutrients collected from tens of thousands of lakes, and ecological-context metrics calculated for all 130,000 continental lakes using geographic information systems and remote sensing datasets. Second, analyses of the database will be conducted for each research question using existing and novel statistical and computer science analytical tools to improve macrosystems ecology knowledge of freshwater nutrients. This award will complement the National Ecological Observatory strengths by providing data for a broader range of aquatic ecosystems and by providing the ecological context for the six continental Observatory lake sites. This award will result in four major intellectual contributions to macrosystems ecology. (1) The identification of regions where coupling and decoupling of nutrients occur, leading to a more comprehensive understanding of relationships between ecological context drivers and linked nutrient cycles. (2) Increased understanding of the types and spatial structure of ecological contexts that are more likely to lead to cross-scale interactions. (3) The identification of the role that novelty in ecological context plays in continental-scale predictions. (4) The transformation of understanding of the ecological contexts that influence biogeochemical cycles at macroscales and lake contributions to these cycles. Given the likely prevalence of such phenomena in other macrosystems, the results will be transferable to other ecosystem types, and more broadly to macrosystems ecology.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12612", "attributes": { "award_id": "2240507", "title": "CAREER: Fast-Charging Energy Storage Devices Enabled by Modulating Internal Electric Field of Heterostructure", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "EPMD-ElectrnPhoton&MagnDevices" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28533, "first_name": "Yue", "last_name": "Zhou", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 199, "ror": "", "name": "University of Texas at Dallas", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Fast-charging capability, as one of the key features of energy storage devices, has drawn extensive interest. It holds great promise to expand or accelerate their applications in many areas, especially for fast-charging electric vehicles to replace internal combustion engine vehicles, as well as stabilizing energy storage from renewable energy sources that are inherently intermittent such as wind and wave energy. However, common energy storage devices, such as batteries, have exhibited severe degradation under fast charging conditions. This Career project is to develop a practical method to develop fast-charging energy storage devices by introducing an internal electric field in the electrode to improve the electrode kinetics and the device performance. The project will host Bootcamp to train rural middle and high school teachers in developing science curricula, equipping them to deliver enriching classroom activities and lectures. Moreover, the project will involve underrepresented students performing science and engineering related projects, especially Native Americans, women, and first-generation college students.The research objective of this Career project aims to develop a novel heterostructure in the electrode to improve the fast-charging capability of energy storage devices by more than 10 times compared with state-of-the-art research studies. Based on the preliminary studies, the central hypothesis is that an internal electric field, generated on the heterointerfaces can accelerate ion transport, enhance electrode kinetics by lowering the energy of activation, and hence improve the performance under fast-charging conditions. It is expected to address this challenge and fundamentally advance the correlation between the electric field of the heterostructure, and the resulting fast-charging performance at the energy storage device level. The major contributions to those multidisciplinary fields lie in several aspects. First, a fundamental understanding will be generated on the effect of the local electric field of the heterostructure on the diffusion coefficient and electrode kinetics. A simulation model will also be created to be integrated with experimental efforts. Second, a knowledge gap will be filled from the material properties of the electrode to the fast-charging functionality of the devices. Third, distinct from conventional nanostructure engineering approaches in state-of-the-art research studies, which have a complex and high-cost fabrication process, introducing a heterostructure in the electrode provides an effective, safe, facile, and transformative approach that remarkably enhances the charge transfer and holds great promise to resolve one of the biggest issues, “long charging time,” of existing energy storage devices. The fundamental study will also open a new door to resolving issues in other energy devices by modulating the electronic structures in the devices.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12613", "attributes": { "award_id": "2222509", "title": "The Young Black Girl: Influencing Science Interest and Commitment to STEM through the Merging of Lived Experiences of Learners in an Out-of-School Program", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "Postdoctoral Fellowships" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28534, "first_name": "Heather", "last_name": "Lavender", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 160, "ror": "", "name": "University of Georgia Research Foundation Inc", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Black women make up the smallest percentage of persons in STEM careers. Girls aged three through fourteen years old, regardless of ethnicity, consider science occupations as unachievable at higher rates than other groups because they sense that these occupations are inappropriate for girls. Prior research also indicates that factors influencing Black girls to consider STEM majors and careers include interest in the science being studied, the learner's own sense of identity, and whether interest can be sustained. This project aims to develop an informal learning program designed as a venue through which Black girls tell STEM educators and researchers about the science activities that propel their interests and participation. The associated study will examine connections between Black girls’ lived experiences and their interest in pursuing STEM careers. Making a “connection” to students’ lived experiences has the potential to decrease the science achievement gap for students historically marginalized in their participation in STEM. The study’s premise is that connecting to science through lived experiences has the potential to support Black girls’ sustained interest in science, and thus increase the potential for them to pursue careers in STEM. The out-of-school program developed in this study will incorporate activities that use low-cost science supplies thereby increasing the curriculum’s potential use in other contexts. This study will recruit Black girls in fourth through sixth grades with various levels of interest in STEM for participation in a summer camp. During the camp, participants will explore the fields of engineering, mathematics, and physical science and learn to use multiplicative and additive comparisons, conduct investigations about matter and sound, and use engineering design processes and scientific inquiry to make connections to their real-life lived experiences. Lived experiences are the experiences, knowledge gained through those experiences, and the ways these experiences inform an individual’s evolving culture. Additionally, participant’s guardians are an important part of their lived experiences. The research study will employ a single-case methodology of off/on/off, quantitatively analyzing surveys and qualitatively analyzing observations, interviews, and artifacts. To inform the analysis of resulting data, the study will adopt a framework of seeking to understand how society organizes itself along intersecting lines of gender, race, class, and other forms of social hierarchies.The project responds to the STEM Education Postdoctoral Research Fellowship (STEM Ed PRF) program that aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12614", "attributes": { "award_id": "2216567", "title": "BPC-DP: Community Outreach Opportunities with Research in Data Science (COORDS)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "CSGrad4US-CISE Grad Fellowshps" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28535, "first_name": "Whelton", "last_name": "Miller", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2121, "ror": "", "name": "Loyola University Stritch School of Medicine", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).To better prepare a data-savvy workforce, universities are increasingly incorporating principles of data science throughout STEM curricula. Emerging teaching practices that encourage students to take a genuine interest in the subject matter and understand the material on a level where they can problem solve can be particularly effective for broadening participation in computing. This partnership between Loyola University, Arrupe College, and the Chicago youth learning organization, MAPSCorps aims to design a data science pathway in Chicago for scholars from underrepresented groups. Through research, training, and mentorship opportunities, undergraduate students, postdoctoral fellows, and faculty will address challenging data science research questions while mentoring the next cohort of scholars. Incorporating principles of computational/data science in STEM curriculums has become more prevalent. Through the programming at the Institute for Racial Justice (IRJ) at Loyola University Chicago, students will be immersed in hands-on experiences throughout the calendar year as well as complemented by an intensive undergraduate summer internship program. As part of IRJ’s pedagogical approach of near-peer mentoring design, the project will recruit undergraduate students to work directly with high school students overseen by an IRJ (Postdoctoral) Fellow in Chicago. In a collaborative effort with the data science programming of the Chicago youth learning organization, MAPSCorps, the project will be centered on experiential STEM learning through structured guidance. The primary objectives of this BPC demonstration project are to 1) create an experience for successful STEM research and learning methods through internships, symposium, and online coursework, providing training opportunities, and seeding research activities, and 2) generate a pipeline of students, particularly underrepresented students from Chicago, who are well prepared for the workforce and will choose to continue their education and training in STEM related disciplines. As a result of the programming with MAPSCorps, this programming will also strengthen the existing informatics and computational science outreach programs in the Chicagoland are by utilizing a group of well-trained faculty and undergraduate researchers with broad expertise as research mentors and instructors.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12615", "attributes": { "award_id": "2146461", "title": "CAREER: Body Modification Technologies", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "HCC-Human-Centered Computing" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28536, "first_name": "Katia", "last_name": "Canepa Vega", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 276, "ror": "", "name": "University of California-Davis", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This project investigates Body Modification Technologies: wearable devices for biosensing through novel form factors with embedded biosensors that interact with body fluids. Current practices for body modification include piercing, tattooing, branding, binding, bodybuilding, and inserting implants. By establishing new collaborations with surgeons, cosmetics companies, beauty salons, and dermatologists, this project investigates placing biosensors on and underneath the skin through body modification materials--lipstick, hair dye, piercings, and tattoos. Biosensors in direct contact with body fluids can significantly improve biological sensing data. This project develops new knowledge about methods and effects of transforming the body into a bio-display, in order to make visible information from metabolism that is usually imperceptible. Potential applications include monitoring illnesses, hormonal changes, dental health, eating disorders, stress tracking, pharmacokinetics, maintaining a culture of health in communities, and sensing changes in environmental factors such as pollution, temperature and UV. Further, the project will collaborate with experts on privacy, safety, and biocompatibility to articulate ethical principles for creating Body Modification Technologies.The Body Modification Technologies project advances wearable computing by developing implementation and evaluation methods to reveal metabolic information by using the form factors of body modifications as a substrate for chromogenic, fluorescence and electrochemical biosensors. This project investigates the design of the electronics, functional algorithms, biotechnology applications, and form factors, e.g., the shape, size, materials, and other physical characteristics that make it possible to wear such devices. Expected outcomes include: (1) fabrication processes for creating the form factors that embed biosensors into body modification materials; (2) design and implementation of hardware and software for devices and mobile applications; (3) dissemination of benchmarking datasets and methods for evaluation of Body Modification Technologies; and (4) derivation of a set of principles and implications on privacy, safety, bio-compatibility, and inclusive design.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12616", "attributes": { "award_id": "2227059", "title": "Collaborative Research: Global eddy-driven transport estimated from in situ Lagrangian observations", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "PHYSICAL OCEANOGRAPHY" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28537, "first_name": "Harper", "last_name": "Simmons", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 159, "ror": "https://ror.org/00cvxb145", "name": "University of Washington", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This project will examine fluid transport by long-lived coherent mesoscale eddies in the global ocean, including volumes within their coherent cores, transiently trapped fluids in eddy peripheries, and stirring effects in the ambient watermasses due to eddy influence therein. The project would rely on a novel eddy-identifying analysis technique (developed in prior work by the PIs) applied to in-situ measurements from global surface drifter dataset and the historical set of acoustically-tracked subsurface floats. This is a departure from the usual approach of eddy detection in gridded satellite products, relying instead on the adaptation of signal processing techniques to float trajectory data. Prior studies based on such gridded products significantly underestimate numbers of eddies, and overestimate eddy sizes and transport of water trapped within them. Data analysis will be supplemented by theoretical idealized and realistic numerical modeling. This work will address what observed ubiquitous coherent eddies actually accomplish in terms of their effect on the large-scale flow. This is a question of societal importance because of its relevance for the development of accurate subgrid-scale parameterizations for general circulation models. The project will advance the boundaries of the viable use of Lagrangian data, and thus provide new tools for eddy examination to the community. The project will support and inform free online courses in fundamental and advanced oceanographic data analysis, so that that these state-of-the-art methodologies will be broadly accessible to the next generation of researchers. The project supports an early career latino scientist, who will develop an undergraduate-level teaching module related to this project.This project will produce a definitive study on the role of coherent eddies in driving fluid transport, taking significant eddy detections from in situ Lagrangian observations as the starting point. The detection method, called vortex signal extraction, recovers time-varying oscillatory signal components from Lagrangian trajectories, without a requirement for the oscillations to be strictly periodic. Available data include approximately 24,000 global surface drifter trajectories plus another 3,000 subsurface trajectories from an historical set of eddy-resolving floats, both NOAA datasets. Data analysis will be complemented by idealized and ultra-high-resolution realistic modeling. These components will be used to explore the subtleties of observing the eddy field from the Lagrangian perspective, to examine the theoretical properties of the eddy detection methods, and to investigate the dynamics of the transport processes of interest. The project will proceed in three branches: (i) dynamics of direct and indirect eddy-driven transport, (ii) the vortex observability problem, and (iii) global estimates. Anticipated products will be new global estimates of coherent eddy properties, populations, and boundaries through statistical modeling informed by an improved understanding of the physics of long-term and transitory trapping. The project will further provide a calibration process by which remotely-sensed features can be more accurately mapped onto fluid structures, and a hydrographic analysis will convert areal transport estimates into mass transports.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12617", "attributes": { "award_id": "2213425", "title": "NSF LEAPS-MPS: Macrocyclic Peptidomimetic Scaffolds for Sensing of Phosphate-containing Metabolites", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "OFFICE OF MULTIDISCIPLINARY AC" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28538, "first_name": "Arundhati", "last_name": "Nag", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 674, "ror": "https://ror.org/04123ky43", "name": "Clark University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). In this project, funded by the Mathematical and Physical Sciences Directorate and housed in the Chemistry Division, Professor Arundhati Nag and her students at Clark University, Worcester, MA will work on designing sensors for phosphate-containing metabolites. Metabolic pathways such as glycolysis use phosphate to form intermediate metabolites, and the levels of the phosphate containing metabolites can provide important information implicated in human diseases such as cancer. The Nag lab will focus on developing sensors for adenosine triphosphate, a nucleoside phosphate metabolite, and for glucose-6-phosphate, a sugar phosphate metabolite, which belong to two different important classes of phosphate-containing metabolites. Underrepresented minority (URM) students will be involved in this research, through summer fellowship and directed studies with Professor Nag. Prof. Nag will also be involved in developing a community of URM students at Clark University thorough mingles, and she and her students will participate in outreach activities and develop workshops for regional high schools.Professor Nag will develop a comprehensive approach for sensing phosphate-containing metabolites by targeting simultaneously both the phosphate moiety and the nucleoside or sugar component attached to the phosphate. The binding motifs will be assimilated into cyclic fluorescent peptidic or peptidomimetic libraries. The libraries will be designed such that they can be easily converted in a one-step reaction to linear analogs that can be readily sequenced using de novo sequencing. The cyclic libraries will be screened for selectively binding the phosphate-containing metabolite of interest, and the hits from the screen, once sequenced, will be studied to help understand which interactions of the sensor with a metabolite are critical for selective detection of metabolites.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12618", "attributes": { "award_id": "2326785", "title": "EAGER: Collaborative Proposal: Probabilistic Scenarios for Megathrust Earthquakes and Tsunami Genesis", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "GVF - Global Venture Fund" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28539, "first_name": "Sui", "last_name": "Tung", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 270, "ror": "https://ror.org/0405mnx93", "name": "Texas Tech University", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Subduction zones, known for parallel chains of towering volcanoes and deep oceanic trenches, host Earth's most geologically complex and heavily populated regions. Subduction zones represent the continuous convergence of two tectonic plates, one of which subducts (“dives”) into the mantle while the other rides over the top of the subducting plate. Stress in this converging system continuously builds until it exceeds the frictional strength of the boundary separating the two plates. At this point, the pent-up stress is released in the form of an earthquake and warps the seafloor. This warping seafloor shifts the overlying ocean surface, a process known as tsunami genesis. Only subduction zones can generate mega-earthquakes, which can warp the seafloor over tremendously vast areas and trigger devastating tsunamis. Predicting tsunamis is a challenging problem because it requires an understanding of the inaccessible details of the stress release along the plate boundary and how it deforms the structure of the entire subduction zone. This research presents a new approach that brings the combined power of mathematics and statistics to bear on this problem. Mathematics describes the physical processes of earthquakes and tsunamis and the statistics account for what is known, or more importantly, what is unknown about the subduction zone system. Results of this research could provide the tools to evaluate risks for coastal locations that are prone to tsunamis. Numerical modeling is the key to this approach and demand for numerical modeling skills is increasing in parallel with expanding data collection initiatives and advances in computational capabilities. This project includes an educational component that will engage students from underrepresented groups in science, technology, engineering, and mathematics in formalized training in numerical modeling. This research will develop numerical tools with a probabilistic perspective to investigate the coupling of seafloor deformation from megathrust earthquakes and tsunamis. These tools will address the challenging problem of embedding sophisticated finite element models of earthquake deformation into automated Monte Carlo sampling strategies. The deformation models will have geodetically-informed slip distributions over curved fault surfaces embedded in domains having the geometric irregularities of topography and bathymetry. Domains will simultaneously account for seismic tomography and reflection models, submarine-based seafloor observations, and tsunami observations. These models will propagate uncertainties from geodetic data into probability density functions for tsunami run-up behavior along coastal locations. This research will, for the first time, quantify how the larger uncertainties for near-trench slip propagate into tsunami predictions. Finite element models are necessary to simulate the complex mechanical behavior of subduction zones and Monte Carlo sampling will reveal how uncertainties in the data and model configurations propagate into deformation and tsunami predictions. These objectives will be achieved using the well-documented 2004 Sumatra megathrust earthquake and tsunami as a case study. A short course on finite element models of earthquake deformation will be developed and delivered. The curriculum will comprise Protocol-based Modeling, Forward Modeling, Inverse Modeling, and discussions of Target Applications. Graduate students from U.S. institutions will be recruited by the Graduate Women In Science chapter and the Women in Science and Engineering program at the South Dakota School of Mines to promote participation of underrepresented students.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12619", "attributes": { "award_id": "2317283", "title": "Promoting Student Success through a Social, Academic, and Institutional Support System in Engineering Education", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "HSI-Hispanic Serving Instituti" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28540, "first_name": "Cole", "last_name": "Joslyn", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 301, "ror": "https://ror.org/0272j5188", "name": "Northern Arizona University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "With support from the Improving Undergraduate STEM Education: Hispanic Serving Institutions (HSI) Program, this Track 2 project will develop and study a sustainable system of academic, institutional, and social supports (i.e., formal peer-mentoring program) for first-year engineering students at the University of Texas El Paso. The Promoviendo el Éxito Estudiantil a través de un Sistema de Apoyo (PromESA) model offers educational and personal support for students by providing mentees with tutoring, advising and connections to available university services. Equally importantly, the project will provide social-emotional support, provide opportunities to build friendships, and affirm students’ sense of belonging, particularly for Latinx students. PromESA components will specifically account for students’ intersecting identities (e.g., gender, first-generation college student status, cultural heritage). Research findings will inform efforts to provide academic, institutional, and social support for under-served populations while addressing the lack of a sense of belonging experienced by Latinx students in engineering education.This project will implement a holistic, socio-culturally responsive peer-mentoring program adapted from the evidence-based Promotores de Educación Program developed at California State University at Long Beach. This multidimensional initiative will be guided by four objectives. First is to increase students’ sense of belonging by incorporating holistic, socio-culturally responsive practices into training and professional development for faculty and peer mentors. Second is to build awareness of Latinx cultural assets and values into the landscape of the piloting department. Third is to increase participating students’ retention, persistence, and academic performance in their engineering degree programs. Fourth is to establish structures and policies to institutionalize major project components beyond the award period. The embedded action research effort will use a combination of qualitative and participatory research methods to offer a fuller understanding of the impact of peer-mentoring programs for students from historically minoritized/marginalized populations. The research will specifically examine how such programs can impact participants and narrow the knowledge gap on the impacts of peer-mentoring programs for Latinx students pursuing engineering degrees, particularly when leveraging their cultural strengths and their intersectional identities. Furthermore, the knowledge generated will provide the engineering education research community with a deeper understanding of the unique experiences and perspectives of Latinx students.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.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1383, "pages": 1419, "count": 14184 } } }