Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1405&sort=-id
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-id", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1419&sort=-id", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1406&sort=-id", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1404&sort=-id" }, "data": [ { "type": "Grant", "id": "471", "attributes": { "award_id": "2142290", "title": "CAREER: Bridging the Gap between Deterministic and Stochastic Structures for Mixed Stochasticity System Design", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 942, "first_name": "Kathryn", "last_name": "Jablokow", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-01", "end_date": "2026-12-31", "award_amount": 250000, "principal_investigator": { "id": 943, "first_name": "Hongyi", "last_name": "Xu", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 257, "ror": "https://ror.org/02der9h97", "name": "University of Connecticut", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 257, "ror": "https://ror.org/02der9h97", "name": "University of Connecticut", "address": "", "city": "", "state": "CT", "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).Systems or products composed of parts that have random (or stochastic) characteristics pose a significant challenge to the design of complex engineering systems. There is a lack of systematic methods for designing artifacts utilizing this type of mixed stochasticity structure. This Faculty Early Career Development Program (CAREER) project will establish a novel computational framework that bridges the gap between random and regular structural patterns to enable: 1) generative design of structures with tailorable stochasticity and desired properties and 2) design of mixed stochasticity structural systems that consist of mixed stochastic structural units to achieve optimal performance. Two sets of engineering applications will be used to evaluate the methodology and demonstrate its benefit to society: design of microstructural materials in energy storage systems and design of a mixed stochasticity structural system for vehicle impact safety. The broader application of the research developments will benefit a wide range of industries, such as high-capacity energy storage materials, structural safety and reliability, and automotive lightweighting, which rely on materials and structures with mixed stochasticity. Furthermore, the results of this research will contribute theories and methodologies that benefit the reliability design of mixed stochasticity systems, such as power grid systems, water distribution systems, and transportation systems. The education and outreach objective of this project is to create a prototype of education-research-industry integration and apply it to K-12 education outreach, outreach to local businesses, and university education. The K-12 education outreach will motivate students to pursue education and careers in science and engineering fields. The outreach to local businesses will assist small businesses and small manufacturers to compete in the post–COVID-19 world. The integration among research, industry practice, and education will strengthen the undergraduate and graduate students’ learning experiences.The overarching research goal of this project is to create a novel computational framework that bridges the gap between deterministic and stochastic structures by establishing a unified design space that covers structural patterns whose stochasticity ranges from random to regular. This framework enables generative design of microstructures/structures with tailorable properties and stochasticity, as well as design of a mixed stochasticity structural system that consists of deterministic and stochastic structural units to achieve optimal performance. This research will transform the discovery and design of structural/microstructural systems in three ways. First, a first-of-its-kind design representation method will be developed for mixed stochasticity structures that will enable the design of structures with tailorable stochasticity. Second, the research will provide a theoretical foundation for transferring knowledge between deterministic and stochastic systems to inspire new designs that achieve target properties. Third, a new design framework will be established for the robustness and reliability-based design of mixed stochasticity structural system. The education and outreach plan includes a Science, Technology, Engineering, Arts, and Math (STEAM) project for K-12 teachers and students in underrepresented minority schools, research dissemination to local small businesses and small manufacturers, and integration among university education, research, and industrial collaboration.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": "470", "attributes": { "award_id": "2127133", "title": "SBIR Phase II: Large-Scale Synthesis of Hollow Metal Nanospheres: Conversion of Batch Synthesis to Continuous Flow", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 940, "first_name": "Elizabeth", "last_name": "Mirowski", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-01", "end_date": "2023-12-31", "award_amount": 991478, "principal_investigator": { "id": 941, "first_name": "Sarah A", "last_name": "Lindley", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 256, "ror": "", "name": "CORELESS TECHNOLOGIES, INC.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 256, "ror": "", "name": "CORELESS TECHNOLOGIES, INC.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase II project is based upon establishing a consistent, reliable source of high-quality hollow metal nanoparticles, thus enabling their commercial adoption in applications where they markedly outperform their conventional counterparts. One such application is point-of-use testing: by switching to hollow metal nanoparticles, lateral flow assays will reach higher levels of sensitivity and lower limits of detection, improving field testing for environmental contamination; detection of toxins and pathogens in agriculture; and early disease identification in clinical and veterinary care. Integration into rapid antibody and antigen tests for highly contagious diseases such as COVID-19 should prove particularly impactful, as the resulting higher sensitivity would reduce the occurrence of false negative results, thereby improving the performance (and public perception) of rapid testing. Critically, it would also improve baseline testing availability for rural and under-served populations who do not have access to PCR-equipped clinical laboratories. They can be applied to many other industries as well. This Small Business Innovation Research Phase II project will advance the state of the art of continuous flow synthesis of plasmonic nanomaterials. Nanoparticle synthesis is a highly sensitive process, and obtaining high quality samples of advanced architectures has previously required labor-intensive, small-batch processes incompatible with large-scale production. Simply scaling traditional batch techniques has led to product with poor quality and prohibitive costs. This project advances a prototype reactor that has demonstrated high-throughput production of hollow plasmonic nanoparticles with control over size and color, while maintaining structural uniformity (<15% CV). Importantly, it reduced the cost of labor per liter of product by 950% from that of small batch synthesis. The proposed project will increase fidelity, further scale production volume, post-process and stabilize the final product, and benchmark its optical performance. The resulting production-scale reactor will have the capacity necessary to supply LFA manufacturers with ready-to-use, advanced color labels. It will enable new research and new nano-enabled devices by creating a consistent commercial supply of high performance plasmonic nanostructures with well-controlled physical properties. The manufacture of hollow metal nanoparticles for point-of-use testing applications will also pave the way for their expansion into other industries that would also benefit from their advantageous optical and photothermal plasmonic properties, such as photocatalysis, water purification, and phototherapeutics.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": "469", "attributes": { "award_id": "2141774", "title": "CAREER: Spectroscopic Exploration of Microscopic Superfluidity", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 938, "first_name": "Christopher", "last_name": "Elles", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-03-01", "end_date": "2027-02-28", "award_amount": 350000, "principal_investigator": { "id": 939, "first_name": "Paul", "last_name": "Raston", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 255, "ror": "https://ror.org/028pmsz77", "name": "James Madison University", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 255, "ror": "https://ror.org/028pmsz77", "name": "James Madison University", "address": "", "city": "", "state": "VA", "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).With support from the Chemical Structure, Dynamics, and Mechanisms-A (CSDM-A) Program in the Division of Chemistry, Paul Raston and his research team at James Madison University will investigate the quantum solvation of small molecules with helium or hydrogen using sophisticated microwave and laser spectroscopy techniques. When liquid helium is cooled to ultra-low temperatures it becomes superfluid, which is a state of matter that is characterized by a variety of peculiar properties. One of these properties is the ability to flow without friction, which implies that if an isolated superfluid is set into rotation, it will continue to rotate indefinitely. This type of frictionless flow was discovered in bulk superfluid helium about 80 years ago, and in tiny droplets (consisting of about 10 helium atoms) about 20 years ago. Surprisingly, the evolution of superfluidity in the realm between tiny droplets and the bulk remains largely unexplored. This CAREER award supports curiosity-driven exploration in this uncharted territory using state-of-the-art spectroscopic techniques. By exploring new manifestations of finite-sized superfluidity, the work aims to provide fresh challenges for theory and seeks to provide for a deeper understanding of quantum chemistry at a fundamental level. The research program also will provide an enriching educational experience for undergraduate student researchers and seeks to attract a diverse body of students into science. Inspired by difficulties associated with online learning during the COVID-19 pandemic, the project also includes an educational component that focuses on developing virtual instrumentation and experiments for teaching modern techniques and approaches in spectroscopy to undergraduate students when in-person classes are not possible, or when the instrumentation is not available.A key intellectual contribution of this work lies in determining the minimum number of helium atoms that are required for superfluidity according to the Landau criterion, which is the traditional criterion for bulk superfluidity. This number is especially important since it corresponds to the transition from the cluster having discrete energy levels to one that has a (quasi) continuum of energy levels, implying that the gap between the energetic properties of small clusters and the bulk has (finally) been bridged. Along the way, it is expected that broad oscillations in the rotational inertia will occur, which are thought to be related to the opening and closing of solvation shells, thus providing detailed structural information regarding microscopic solvation. Another significant contribution involves exploring how nanoscopic surfaces are wetted by investigating the quantum solvation of small aromatics with helium. The spectra of these systems provide information about how the helium fluid coats the surfaces, and about how the superfluid behavior evolves with cluster size. Finally, Dr. Raston and his research team are investigating quantum solvation by fermions (deuterium hydride) in order to experimentally test whether the previously reported decoupling of boson (helium or hydrogen) density from molecular rotation is indeed an indicator of microscopic superfluidity. The educational dimension of this project is inspired by the difficulties associated with delivering upper-division laboratory courses online. To help alleviate these challenges and to make experiments possible for those who do not have access to the required scientific instrumentation, a suite of modern virtual instruments is being developed. The user-friendly interface is designed to engage and guide students through a variety of experiments that will be made freely available on the web so that users can easily access them. The virtual instruments will provide a platform for learning about data acquisition in an autonomous environment, while also fostering an improved understanding of instrument control and developing student intuition about instrument operation.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": "468", "attributes": { "award_id": "2136554", "title": "SBIR Phase II: Remote Monitoring of Patients in Respiratory Distress", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 936, "first_name": "Henry", "last_name": "Ahn", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-01", "end_date": "2023-12-31", "award_amount": 1000000, "principal_investigator": { "id": 937, "first_name": "Alireza", "last_name": "Akhbardeh", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 254, "ror": "", "name": "CEREVU MEDICAL, INC.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 254, "ror": "", "name": "CEREVU MEDICAL, INC.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to advance a real-time assessment system for patients at risk of respiratory distress. The goal is to monitor these patients and avoid hospital admissions or re-admissions for previously discharged patients. The first envisioned application is monitoring of Chronic Obstructive Pulmonary Disease (COPD), for which there is no cure - but the disease can be managed with diligent surveillance. The envisioned remote patient monitoring system will enhance patient care and outcomes by providing early warning of COPD flare-ups, thus reducing the need for emergency hospital visits and admissions. This system will provide healthcare workers and caregivers added time to implement protocols, such as inhaler-based drug delivery, thus reducing critical events for COPD, as well as COVID-19, asthma, pneumonia, and other respiratory illnesses. This Small Business Innovation Research (SBIR) Phase II project is to develop a reusable device monitoring biomarkers of nociceptive pain, dyspnea, and coughing dynamics, along with traditional vital sign measurements. The project will develop a reusable device with a rechargeable battery and replaceable adhesives for prolonged use during the duration of the monitoring period. Additionally, the user interface will be optimized for the display of pertinent symptoms to the patient, caregivers, and medical personnel providing remote care from a centralized monitoring center. The efficient sharing of continuous changes in patient status will allow for the most effective personalized treatment. The project will develop a system with appropriate cybersecurity protocols.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": "467", "attributes": { "award_id": "2139816", "title": "Keeping Shelters in Place: Understanding the Impacts of Residential Landlord Decision-Making on Post-Disaster Housing Stability", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 931, "first_name": "Daan", "last_name": "Liang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-11-01", "end_date": "2024-10-31", "award_amount": 651420, "principal_investigator": { "id": 935, "first_name": "Jane", "last_name": "Rongerude", "orcid": "https://orcid.org/0000-0002-6562-3861", "emails": "[email protected]", "private_emails": "", "keywords": "['Qualitative methods']", "approved": true, "websites": "['https://www.design.iastate.edu/faculty/jrong/']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 192, "ror": "https://ror.org/04rswrd78", "name": "Iowa State University", "address": "", "city": "", "state": "IA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 932, "first_name": "Elizabeth", "last_name": "Mueller", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 933, "first_name": "Lily", "last_name": "Wang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 934, "first_name": "Daniel", "last_name": "Kuhlmann", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 192, "ror": "https://ror.org/04rswrd78", "name": "Iowa State University", "address": "", "city": "", "state": "IA", "zip": "", "country": "United States", "approved": true }, "abstract": "This research is responding to the local threats to rental housing security that emerged during the COVID-19 pandemic. Rental housing occupies a significant portion of the housing stock in US metropolitan areas, yet researchers know very little about the specific characteristics of the institutional and non-institutional entities that hold titles to those properties and determine housing supply, rents, and the conditions of both buildings and units. To further complicate this scenario, regulatory environments and rental housing market dynamics vary greatly across space, both within and between metropolitan regions. Resiliency, the ability to withstand and recover from a disaster or a shock, is shaped by the conditions of the local housing market and the associated regulatory environment. However, it is also shaped by the behaviors of the landlord population operating within that milieu. In the absence of existing knowledge about landlord characteristics, behaviors, and needs, cities and policy makers responding to disasters are left guessing how to stabilize their rental markets, keep renters housed, deliver meaningful assistance to property owners, and plan for an effective post-disaster recovery. This study contributes to the progress of science by investigating rental property owner characteristics and identifying meaningful rental owner categories as they relate to disaster and post-disaster decision-making. It contributes to the national health, prosperity and welfare by linking that knowledge to disaster-related rental housing outcomes in specific places. The COVID-19 pandemic has demonstrated that the security of the rental housing market is intertwined with a landlord’s ability to tackle financial challenges. The decisions that landlords make in the midst of a disaster affect not only their tenants’ ability to remain housed, but the ability of the city to respond to and recover from the event and ensure future housing stability.The central hypothesis of this study is that when responding to disasters, non-institutional rental property owners make property and investment decisions that accelerate ownership consolidation and reduce post-disaster housing security within communities. The research is structured as a longitudinal study using an innovative, convergent approach that brings together social science and data science in order to create new datasets and tools for data analysis. It fills a major gap in existing knowledge by investigating landlord decision-making across the stages of the disaster management cycle and identifying meaningful categories of non-institutional rental property owners based on landlord characteristics. This study sets out to answer not just who landlords are, but how they respond to disasters and how disaster-induced changes in the landlord population might continue to affect the built environment of cities and communities into the future. There are two nested research efforts within this proposal: to understand landlord characteristics and decision-making within the context of the post-pandemic recovery and potential future shocks or disasters; and, through data science approaches, to identify and characterize the landlord population and the potential value of better data utilization for promoting rental housing security during local recovery from hazard-related shocks and stresses. The overall project goals to improve housing outcomes within local disaster recovery efforts draw from the domain of social science including planning, sociology, economics, and finance. The project goals to create tools that improve the local institutional capacity for identifying and communicating with landlords rely on the domain of data science research. This project’s integrative methodology strengthens the capacity of each domain, generating an innovative approach where social science research is able to resolve the enduring problem of landlord invisibility and the data science techniques are refined through their application to real world problems. The unit of analysis for this study is the rental property owner, specifically non-institutional investors, in nine mid-sized US cities. These cites, though of similar size, have varied housing stocks, socioeconomic characteristics, and political orientations. They also provided unique state and local responses to the COVID housing crisis. Five of the cities are located in states that are part of the Gulf Coast region. All have either been recently affected by hazard-related disasters or are at high risk of experiencing a disaster. This chronological range of disaster experience and recovery will allow the tracking of landlord perspectives across the disaster management cycle.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": "466", "attributes": { "award_id": "2153919", "title": "RAPID/Collaborative Research: Examining Household Movements and Evacuation Decision-Making in a Compounding Risk Event", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 929, "first_name": "Daan", "last_name": "Liang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-01", "end_date": "2022-12-31", "award_amount": 49142, "principal_investigator": { "id": 930, "first_name": "Laura", "last_name": "Siebeneck", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 253, "ror": "https://ror.org/00v97ad02", "name": "University of North Texas", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 253, "ror": "https://ror.org/00v97ad02", "name": "University of North Texas", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "Selecting protective actions in response to hurricane threats can be a challenging process for households. Adding to the complexity of this process are the risks stemming from the ongoing COVID-19 pandemic and the compounding risks posed by lingering utility outages, high heat, and the remnants of Hurricane Nicholas in the weeks following Hurricane Ida. While many studies have examined protective action decisions of households in response to natural and human-induced risks, less is known about this process in instances where households face simultaneous disasters and compounding risks. The purpose of this Grants for Rapid Response Research (RAPID) collaborative project is to examine household protective action decisions during two simultaneous events: Hurricane Ida and the ongoing COVID-19 pandemic. Time-sensitive data gathered through online, phone, and mail surveys and supplemented with GPS/mobile phone data will be used to examine household protective action decision-making and mobility patterns before, during, and after Hurricane Ida. The findings from this project are expected to save lives and minimize stress during evacuations and return trips. Additionally, the findings of the research will benefit the emergency management community and society as new knowledge related to protective action decisions during simultaneous hazard events can help maximize safety and efficiency in coordinating and managing the movements of displaced residents.Decisions pertaining to whether one evacuates or shelters, where to evacuate to, and when to return after a disaster all entail consideration of multiple factors related to risks, warning messages, household socio-demographic characteristics, and available resources. While numerous studies examine these decisions in the context of a single hazard scenario, very little is known as to how protective action decisions are selected during simultaneous disaster events. Furthermore, the nature of tradeoffs and their impact on decisions during dual risk scenarios are not well understood. The goal of this study is to collect ephemeral data to examine household decision-making during Hurricane Ida and the ongoing COVID-19 pandemic. By advancing the Protective Action Decision Model, this study will gather household data using surveys and GPS mobile phone data that will allow the understanding of three primary research questions: 1. How do households make evacuation, sheltering, post-event relocation and return-entry decisions during simultaneous disasters? 2. What factors influence evacuation and return-entry timing and the selection of evacuation destinations? Similarly, what factors influence shelter-in-place decisions? 3. What is the nature of the multiple movements undertaken by households throughout the response and short-term recovery process? This project will advance theory pertaining to protective action decision-making during simultaneous disaster events and provide important insights into how risk tradeoffs inform these decisions. Specifically, new knowledge will be generated through: 1) gathering ephemeral data of household movements and protective action decisions undertaken during Hurricane Ida and the ongoing COVID-19 pandemic in order to advance understanding of this dynamic process; 2) documenting locations household move to during the disaster response and short-term recovery phases and why these locations were selected, and 3) providing new insights into how households perceive the tradeoffs in risks when making decisions during simultaneous disasters. Findings from this study will offer a more nuanced understanding of household decisions and movements in response to disasters and provide better insight into the experiences of displaced households during and after disasters.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": "465", "attributes": { "award_id": "2204924", "title": "RAPID: Agenda Generality and Behavior in Social Network Interactions about COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 927, "first_name": "Robert", "last_name": "O'Connor", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-10-01", "end_date": "2022-10-31", "award_amount": 100548, "principal_investigator": { "id": 928, "first_name": "Dolores", "last_name": "Albarracin", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 232, "ror": "https://ror.org/00b30xv10", "name": "University of Pennsylvania", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 232, "ror": "https://ror.org/00b30xv10", "name": "University of Pennsylvania", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "The same types of social networks that transmit the COVID-19 disease may be leveraged to spread healthy norms and positive behaviors. This research gathers important, time-sensitive data to understand the conditions under which digital social networks can influence health behaviors relevant to the COVID-19 pandemic and how to reduce negative social influences in digital environments. At a time when people spend unprecedented amounts of time on digital networks, public health strategies deployed in these networks may shape the health and social outcomes of Americans in the next 12 months. This research advances understanding of these public health strategies.The project’s theory is that discussing either general or specific issues (e.g., curbing COVID-19 disease or wearing a mask) can have important consequences on the spread of risky attitudes and behaviors through a network. The research entails (a) an ecological study of Twitter and Instagram networks and (b) experiments manipulating the mix of healthy and risky behaviors promoted in the network and the focus of the discussion on either general or specific issues. The project generates public health recommendations and algorithms to improve health discussions on social media. The investigators use a dynamic panel data model to predict individual behavior from the individual’s own attitudes and own past behaviors as well as the behaviors of other members of their network. The research team uses graph convolutional networks both to capture richer network aspects and to model sparse networks.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": "464", "attributes": { "award_id": "2153913", "title": "RAPID/Collaborative Research: Examining Household Movements and Evacuation Decision-Making in a Compounding Risk Event", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 925, "first_name": "Daan", "last_name": "Liang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-01", "end_date": "2022-12-31", "award_amount": 50000, "principal_investigator": { "id": 926, "first_name": "Satish", "last_name": "Ukkusuri", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 252, "ror": "", "name": "Purdue University", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 252, "ror": "", "name": "Purdue University", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true }, "abstract": "Selecting protective actions in response to hurricane threats can be a challenging process for households. Adding to the complexity of this process are the risks stemming from the ongoing COVID-19 pandemic and the compounding risks posed by lingering utility outages, high heat, and the remnants of Hurricane Nicholas in the weeks following Hurricane Ida. While many studies have examined protective action decisions of households in response to natural and human-induced risks, less is known about this process in instances where households face simultaneous disasters and compounding risks. The purpose of this grant for Rapid Response Research (RAPID) collaborative project is to examine household protective action decisions during two simultaneous events: Hurricane Ida and the ongoing COVID-19 pandemic. Time-sensitive data gathered through online, phone, and mail surveys and supplemented with GPS/mobile phone data will be used to examine household protective action decision-making and mobility patterns before, during, and after Hurricane Ida. The findings from this project are expected to save lives and minimize stress during evacuations and return trips. Additionally, the findings of the research will benefit the emergency management community and society as new knowledge related to protective action decisions during simultaneous hazard events can help maximize safety and efficiency in coordinating and managing the movements of displaced residents.Decisions pertaining to whether one evacuates or shelters, where to evacuate to, and when to return after a disaster all entail consideration of multiple factors related to risks, warning messages, household socio-demographic characteristics, and available resources. While numerous studies examine these decisions in the context of a single hazard scenario, very little is known as to how protective action decisions are selected during simultaneous disaster events. Furthermore, the nature of tradeoffs and their impact on decisions during dual risk scenarios are not well understood. The goal of this study is to collect ephemeral data to examine household decision-making during Hurricane Ida and the ongoing COVID-19 pandemic. By advancing the Protective Action Decision Model, this study will gather household data using surveys and GPS mobile phone data that will allow the understanding of three primary research questions: 1. How do households make evacuation, sheltering, post-event relocation and return-entry decisions during simultaneous disasters? 2. What factors influence evacuation and return-entry timing, the selection of evacuation destinations, and shelter-in-place decisions? 3. What is the nature of the multiple movements undertaken by households throughout the response and short-term recovery process? This project will advance theory pertaining to protective action decision-making during simultaneous disaster events and provide important insights into how risk tradeoffs inform these decisions. Specifically, new knowledge will be generated through: 1) gathering ephemeral data of household movements and protective action decisions undertaken during Hurricane Ida and the ongoing COVID-19 pandemic in order to advance understanding of this dynamic process; 2) documenting locations household move to during the disaster response and short-term recovery phases and why these locations were selected, and 3) providing new insights into how households perceive the tradeoffs in risks when making decisions during simultaneous disasters. Findings from this study will offer a more nuanced understanding of household decisions and movements in response to disasters and provide better insight into the experiences of displaced households during and after disasters.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": "463", "attributes": { "award_id": "2204662", "title": "RAPID: Collaborative Research: Metapopulation Modeling to Develop Strategies to Reduce COVID-19 Transmission in Public Spaces", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 923, "first_name": "Katharina", "last_name": "Dittmar", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-10-01", "end_date": "2023-05-31", "award_amount": 25296, "principal_investigator": { "id": 924, "first_name": "Davida", "last_name": "Smyth", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 251, "ror": "", "name": "Texas A&M University-San Antonio", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 251, "ror": "", "name": "Texas A&M University-San Antonio", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic presents an unprecedented challenge to public and private institutions to safely reopen public spaces, including workspaces and schools. However, we have little guidance on how to manage the use of shared spaces in light of a highly transmissible, but invisible, pathogen. The fundamental aim of this project is to better understand how SARS-CoV-2 spreads in built environments. Predictions generated by mathematical modeling will be experimentally tested using a surrogate non-pathogenic virus. This project presents a new paradigm where the likelihood of infected individuals being present, the amount and manner of viral shedding, the locations of viruses over time, and the usage-needs of a location provide for a major advancement in the assessment of public space occupancy and usage. The ultimate goal is to develop practices capable of limiting virus transmission and meeting the current worldwide challenge to public health. Recommendations will resemble established building and fire codes, which regulate how space is allotted per occupant based upon design and usage requirements; our analyses will generate a “COVID Code” that can be generalized for use during future outbreaks. This research will also provide training opportunities for students and postdoctoral scholars. A recently developed computational model (the Ephemeral Island Metapopulation Model (EIMM)) that applies metapopulation theory to explain how pathogens persist in hospital environments will be revised to address the spatial spread of SARS-CoV-2 within built environments. The EIMM defines aspects of the built environment as distinct habitable zones of occupancy (“demes”) in much the same manner as human hosts are considered, but these demes have their own biological parameters relevant to the survival and transmission of SARS-CoV-2. The number and size of both living and non-living demes, instead of human hosts alone, are used to model size and location of pathogen populations using ecologically relevant parameters, such as growth rate, population size, and carrying capacity. An enveloped bacteriophage phi6 will be used to validate model expectations as well as test control strategies in real environments such as classrooms. The goal is to test which interventions suggested by the EIMM minimize opportunities for phage phi6 spread in shared spaces, and this information can be adapted to provide estimates of how various interventions would affect SARS-CoV-2 persistence and transmission.This RAPID award is made by the Ecology and Evolution of Infectious Diseases Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.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": "462", "attributes": { "award_id": "2136508", "title": "SBIR Phase I: Ace2 decoy as a pan-coronavirus therapeutic (COVID-19)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 921, "first_name": "Kaitlin", "last_name": "Bratlie", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-01", "end_date": "2022-12-31", "award_amount": 256000, "principal_investigator": { "id": 922, "first_name": "Gabriel Glenn A", "last_name": "Gregorio", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 250, "ror": "", "name": "WHITE ROCK THERAPEUTICS", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 250, "ror": "", "name": "WHITE ROCK THERAPEUTICS", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the advancement of a patient-friendly and cost-effective way to prevent and treat COVID-19 infection arising from SARS-CoV-2 and its variants. The inability to quickly stop the spread of respiratory infectious pathogens can have devastating global consequences, resulting in millions of deaths and creating an enormous economic burden. This project will prove the viability of an aerosolized pan-coronavirus neutralizing agent that can be delivered directly to the lungs, either as an early-stage, post-infection treatment or as a prophylactic. An inhalable therapeutic has a stronger commercial potential than the currently approved monoclonal antibodies which require intravenous delivery, and this drug will be more likely to retain potency against future variants. The COVID-19 virus is expected to persist in the human population, and novel variants thereof will continue to emerge. Therefore, this technology could be crucial in addressing these ongoing medical needs.This Small Business Innovation Research (SBIR) Phase I project aims to demonstrate in vivo efficacy of an inhalable decoy receptor that would effectively inhibit SARS-CoV-2 interaction with its endogenous cellular target and thus prevent infection of the host. The mechanism of SARS-CoV-2 viral entry into respiratory epithelial cells depends on the binding of viral Spike trimer to the host Ace2 receptor. The decoy receptor approach would use a recombinant soluble version of the Ace2 receptor that would bind and coat the viral particle, competing for Spike interaction with endogenous Ace2 and thus prevent virus docking to the cell surface. Stabilizing mutations in the Ace2 protein could enable it to act as a decoy receptor and also have sufficient stability in an inhalable formulation, allowing it to be deployed directly to the respiratory tract via a nebulizer. The dependence on Ace2 receptor binding is a potential Achilles heel of coronaviruses, as it is unlikely that SARS-CoV-2 or similar coronaviruses can mutate around the requirement to interact with this host protein.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": 1405, "pages": 1419, "count": 14184 } } }