Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1383&sort=-principal_investigator
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-principal_investigator", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=-principal_investigator", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1384&sort=-principal_investigator", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1382&sort=-principal_investigator" }, "data": [ { "type": "Grant", "id": "7187", "attributes": { "award_id": "3R01GM127512-01A1S1", "title": "Regional Healthcare Ecosystem Analyst (RHEA) Modeling the Environment (MODE): SARS-CoV-2", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 7693, "first_name": "Veerasamy", "last_name": "Ravichandran", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-04", "end_date": "2024-05-31", "award_amount": 322626, "principal_investigator": { "id": 1584, "first_name": "Bruce Y", "last_name": "Lee", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 367, "ror": "https://ror.org/01d03cj21", "name": "Research Foundation of The City University of New York", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1070, "ror": "", "name": "GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "With the ongoing COVID-19 coronavirus pandemic, the potential environmental transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of significant concern, especially in hospitals. Choosing and coordinating the right approaches (e.g., environmental cleaning and monitoring, airflow regulation) in the complex hospital environment can be challenging, given frequent patient and staff turnover, limited resources, and the potential rapid spread of SARS-CoV-2. Further, developing new approaches requires guidance for design and implementation. Computational modeling with economic, operational, and epidemiologic components can assess the value of approaches with various features and efficacies to guide design and implementation in complex systems. Our Regional Healthcare Ecosystem Analyst (RHEA) Modeling the Environment (RHEA-MODE) project already will be developing agent-based models (ABMs) to help better understand and prevent the environmental transmission of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE), two pathogens that commonly cause healthcare-associated infections (HAIs). This offers a key opportunity to ask and answer similar questions about SARS-CoV-2. Therefore, the goal of this proposed RHEA-MODE: SARS-CoV-2 supplemental project is to develop ABMs of hospitals to help better understand the role of the hospital environment and environmental cleaning and monitoring methods in preventing and controlling the spread of SARS-CoV-2. While there may be some similarities with MRSA and VRE, the characteristics (e.g., contact, air transmission) and consequences (e.g., various COVID-19 outcomes) of SARS-CoV-2 are different, requiring different representations in the ABMs. The virus also requires different interventions (e.g., N95 mask use) and potentially different environmental cleaning (e.g., more aggressive standard disinfectant use, new procedures like ultraviolet light irradiation, air filtering) and monitoring (e.g., checking compliance with cleaning protocols and for the presence of virus in the air and on surfaces). Our team is led by Bruce Y. Lee, MD MBA, who has been part of the Models of Infectious Disease Agent Study (MIDAS) network for over 12 years and has over two decades of experience in industry and academia leading large mathematical and computational modeling projects to better understand, prevent, and control infectious diseases, including being embedded in the U.S. Department of Health Human Services during the H1N1 flu pandemic to assist the national response. Specific Aim 1 for this project will develop detailed computational representations of sample hospitals and their environments and determine the role of the hospital environment in the transmission of SARS-CoV-2 under various conditions and circumstances. Specific Aim 2 will explore how various environmental cleaning and monitoring products, methods, approaches, and strategies can reduce SARS-CoV-2 transmission, spread, and associated health and economic outcomes based upon the simulation models from Aim 1.", "keywords": [ "2019-nCoV", "Academia", "Address", "Affect", "Air", "Air Movements", "Area", "COVID-19", "Characteristics", "Clinical", "Communicable Diseases", "Complex", "Computer Models", "Coronavirus", "Development", "Disease Outbreaks", "Disinfectants", "Economic Models", "Economics", "Ecosystem", "Environment", "Epidemic", "Epidemiology", "Equipment", "Funding Opportunities", "Goals", "Health care facility", "Healthcare", "Hospitals", "Hydrogen Peroxide", "Industry", "Influenza A Virus H1N1 Subtype", "Intervention", "Location", "Masks", "Methods", "Modeling", "Monitor", "National Institute of General Medical Sciences", "Operations Research", "Outcome", "Patients", "Policies", "Principal Investigator", "Procedures", "Protocols documentation", "Public Health Informatics", "Regulation", "Resources", "Role", "Sampling", "Surface", "System", "Technology", "Ultraviolet Rays", "United States Dept. of Health and Human Services", "Vancomycin resistant enterococcus", "Virus", "Work", "air filter", "base", "design", "economic impact", "economic outcome", "experience", "health economics", "healthcare-associated infections", "infectious disease model", "innovation", "insight", "irradiation", "mathematical model", "member", "methicillin resistant Staphylococcus aureus", "models and simulation", "novel strategies", "pandemic disease", "pandemic influenza", "pathogen", "prevent", "response", "transmission process", "ultraviolet irradiation", "vapor" ], "approved": true } }, { "type": "Grant", "id": "9405", "attributes": { "award_id": "1R01HS028165-01", "title": "MOdeling Nursing homes to Affect Response to COVID-19 (MONARC)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 24670, "first_name": "Leyi", "last_name": "Lin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-03", "end_date": "2022-11-30", "award_amount": 500000, "principal_investigator": { "id": 1584, "first_name": "Bruce Y", "last_name": "Lee", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 367, "ror": "https://ror.org/01d03cj21", "name": "Research Foundation of The City University of New York", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1070, "ror": "", "name": "GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Nursing homes have been hit particularly hard by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. NHs may serve as epicenters of transmission that could continue to help fuel the overall pandemic because they are critical parts of complex, interconnected networks of health facilities in a region. However, determining how best to prevent/control the transmission of SARS-CoV-2 in nursing homes can be challenging. A NH itself is a complex system, consisting of NH residents/staff/visitors that mix with each other in different ways throughout a given day. Since NHs and the ecosystems that they sit within are complex systems, computational modeling that integrates economic, operational, and epidemiologic aspects of SARS- CoV-2 can provide decision makers with important insights on how best to prevent the spread of SARS-CoV-2 within NHs and throughout the surrounding region. The overall goal of this proposed project, MOdeling Nursing homes to Affect Response to COVID-19 (MONARC), is to develop agent-based models (ABMs) of the 70 NHs in OC and use these models to help design and evaluate various SARS-CoV2 policies and interventions (e.g., screening, testing, and cohorting strategies for NH residents, NH staff and visitors). Furthermore, the project will develop a new computational tool that NH administrators and public health officials and policymakers in other regions can then use to build models of their NHs to use to make decisions about COVID-19 prevention and response. This project will be led by two seasoned investigators and their teams who have worked together for over a decade on developing ABMs to prevent/control the spread of infectious diseases in healthcare facilities. Since 2007, this has included helping decision makers address nearly every major infectious disease threat to the U.S., including being embedded in Health and Human Services (HHS) during the 2009 H1N1 epidemic. This project will be a natural extension of our past projects and our current COVID-19 coronavirus modeling work. Specific Aim 1 will develop ABMs of the 70 NHs in OC to evaluate the impact of different SARS-CoV-2 symptom screening and COVID-19 testing strategies such as the timing, frequency, and test types. Specific Aim 2 will explore the value of various strategies to cohort COVID-19-positive NH residents and the staff who care for them, within and across different NHs. Specific Aim 3 will develop a computational tool that can simultaneously evaluate symptom screening, testing, and cohorting strategies to address COVID-19 in NHs, accounting for local prevalence, facility size, and adherence to infection prevention standards. The MONARC project will bring multiple innovations including: 1) addressing urgent but currently unaddressed questions about what NHs can do to prevent/control the spread of SARS-CoV-2, 2) determining how SARS-CoV-2 prevention and control strategies should be tailored by different NHs and NH resident and staff characteristics and 3) developing a computational tool that NHs can use to help determine the best strategies in response to SARS-CoV-2.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "9406", "attributes": { "award_id": "5R01HS028165-02", "title": "MOdeling Nursing homes to Affect Response to COVID-19 (MONARC)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 24670, "first_name": "Leyi", "last_name": "Lin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-03", "end_date": "2022-11-30", "award_amount": 493471, "principal_investigator": { "id": 1584, "first_name": "Bruce Y", "last_name": "Lee", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 367, "ror": "https://ror.org/01d03cj21", "name": "Research Foundation of The City University of New York", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1070, "ror": "", "name": "GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Nursing homes have been hit particularly hard by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. NHs may serve as epicenters of transmission that could continue to help fuel the overall pandemic because they are critical parts of complex, interconnected networks of health facilities in a region. However, determining how best to prevent/control the transmission of SARS-CoV-2 in nursing homes can be challenging. A NH itself is a complex system, consisting of NH residents/staff/visitors that mix with each other in different ways throughout a given day. Since NHs and the ecosystems that they sit within are complex systems, computational modeling that integrates economic, operational, and epidemiologic aspects of SARS- CoV-2 can provide decision makers with important insights on how best to prevent the spread of SARS-CoV-2 within NHs and throughout the surrounding region. The overall goal of this proposed project, MOdeling Nursing homes to Affect Response to COVID-19 (MONARC), is to develop agent-based models (ABMs) of the 70 NHs in OC and use these models to help design and evaluate various SARS-CoV2 policies and interventions (e.g., screening, testing, and cohorting strategies for NH residents, NH staff and visitors). Furthermore, the project will develop a new computational tool that NH administrators and public health officials and policymakers in other regions can then use to build models of their NHs to use to make decisions about COVID-19 prevention and response. This project will be led by two seasoned investigators and their teams who have worked together for over a decade on developing ABMs to prevent/control the spread of infectious diseases in healthcare facilities. Since 2007, this has included helping decision makers address nearly every major infectious disease threat to the U.S., including being embedded in Health and Human Services (HHS) during the 2009 H1N1 epidemic. This project will be a natural extension of our past projects and our current COVID-19 coronavirus modeling work. Specific Aim 1 will develop ABMs of the 70 NHs in OC to evaluate the impact of different SARS-CoV-2 symptom screening and COVID-19 testing strategies such as the timing, frequency, and test types. Specific Aim 2 will explore the value of various strategies to cohort COVID-19-positive NH residents and the staff who care for them, within and across different NHs. Specific Aim 3 will develop a computational tool that can simultaneously evaluate symptom screening, testing, and cohorting strategies to address COVID-19 in NHs, accounting for local prevalence, facility size, and adherence to infection prevention standards. The MONARC project will bring multiple innovations including: 1) addressing urgent but currently unaddressed questions about what NHs can do to prevent/control the spread of SARS-CoV-2, 2) determining how SARS-CoV-2 prevention and control strategies should be tailored by different NHs and NH resident and staff characteristics and 3) developing a computational tool that NHs can use to help determine the best strategies in response to SARS-CoV-2.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "690", "attributes": { "award_id": "2036463", "title": "SBIR Phase I: Improved COVID-19 Testing by Rapid Sample Purification", "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": 1581, "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": "2020-12-15", "end_date": "2022-03-31", "award_amount": 256000, "principal_investigator": { "id": 1582, "first_name": "Ting-Pau", "last_name": "Oei", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 366, "ror": "", "name": "XMD DIAGNOSTICS, LLC", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 366, "ror": "", "name": "XMD DIAGNOSTICS, LLC", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is an improved reliability for coronavirus detection. The proposed project will develop a tissue purification technology to extract (purify) virus from patient samples. Purer samples (more coronavirus, less confounding materials) is anticipated to improve signal from virus and reduce signal from non-virus materials, and is therefore anticipated to improve the reliability of testing (fewer false positives and false negatives). This can potentially impact the social distancing of the pandemic. This Small Business Innovation Research (SBIR) Phase I project of a system to extract purified samples for coronavirus testing for downstream testing, such as PCR-based analysis. The system is a novel purification technology that uses biological (antibodies) and other physical to quickly and reliably extract target microorganisms (here COVID viruses) from human samples.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": "689", "attributes": { "award_id": "2033909", "title": "SBIR Phase I: COVID-19: Robots for Automating Indoor Disinfection Tasks with Existing Non-Autonomous Devices", "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": 1579, "first_name": "Muralidharan", "last_name": "Nair", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-01", "end_date": "2021-12-31", "award_amount": 253836, "principal_investigator": { "id": 1580, "first_name": "Bradley", "last_name": "Oosterveld", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 365, "ror": "", "name": "Thinking Robots Inc.", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 365, "ror": "", "name": "Thinking Robots Inc.", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to fully automate frequent and regular disinfection tasks in hospitals, care centers, commercial units, universities, schools, and other indoor spaces. This task has become critically important in light of the rapid spread of SARS-CoV-2. By being fully automated, the proposed robotic system reduces human risk and required protective gear (as humans do not need to enter a contaminated zone to move in and position their devices) as well as human workload (due to autonomous operation of the robot system). Current Ultra-Violet C (UVC) disinfection robots utilize integrated bulbs and have limited operation intervals due to the need to frequently recharge, the proposed solution is able to operate a wide variety of disinfection devices like UVC lamps, High-Efficiency Particulate Air (HEPA) filters, hydrogen peroxide aerosols, and others, and thus, offers maximum versatility to the customer while also allowing for the utilization of the customer’s existing devices. In addition, the assistive system can be instructed in natural language by non-experts and can thus be operated without prior training.This Small Business Innovation Research (SBIR) Phase I project will develop two autonomous robots that, together, can carry out room disinfection tasks with existing equipment. One challenge with automating disinfection, especially UVC disinfection, is the power consumption of UVC lights and the need for frequent recharging of battery-operated units on autonomous robots. Another is that current robotic solutions have UVC devices integrated, which prevents the use of existing or custom devices. The solution to both challenges is to build a flat carrier robot where existing or custom devices can be mounted and a second robot, tethered to the carrier robot, that can power the device by docking at a purpose-made docking station connected to a wall outlet. While the device is on, both robots will also be able to recharge their batteries and thus operate continuously. Advanced navigation strategies are necessary to ensure that both robots can drive through indoor environments to their target locations without tangling the tether. Both robots will be equipped with laser and camera sensors and utilize joint sensor information communicated via their tether for improving localization and navigation. The result will be a robust autonomous multi-robot system for navigation and disinfection tasks.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": "688", "attributes": { "award_id": "2102193", "title": "NCSE Drawdown 2021: Research to Action: Science and Solutions for a Planet Under Pressure", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [], "program_officials": [ { "id": 1577, "first_name": "Brandon", "last_name": "Jones", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-15", "end_date": "2021-11-30", "award_amount": 59947, "principal_investigator": { "id": 1578, "first_name": "Erica", "last_name": "Goldman", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 364, "ror": "", "name": "National Council for Science and the Environment/CEDD", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 364, "ror": "", "name": "National Council for Science and the Environment/CEDD", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true }, "abstract": "The National Council for Science and the Environment (NCSE) Drawdown 2021 Conference on Research to Action: Science and Solutions for a Planet Under Pressure positions itself to have broader impact through framing, design, implementation, and post-conference engagement and collaboration. In particular, the partnership with Project Drawdown ensures weaving together of two networks focused on enhancing science and solutions that otherwise may not have connected. NCSE has deep expertise in both the theory and practice of evidence-use in decision making and knowledge on how to design interactions to promote effective “boundary spanning,” the process that ensures that the knowledge that is produced is actually useful to decision-makers, and accessible at the right time and in the right format. As with other NCSE conferences, this event is designed to optimize strategic dialogue among communities with the goal of generating solution-based outcomes. NCSE is working to design a conference that exemplifies “convergence-in-action,” tapping into the transformational potential of one of NSF’s 10 Big Ideas. Through the partnership with Project Drawdown, emergent research questions will help catalyze the solutions-driven focus in the second half of the conference.This proposal requests support for the 2021 NCSE Annual Conference which plans to emphasize a systems-approach to the effects of heat, water, and the COVID-19 pandemic as a threat multiplier -examining both impacts and solutions. NCSE 2021, Research to Action: Science and Solutions for a Planet Under Pressure, will explore the links between the changes in Earth’s physical systems and its social institutions. The primary objectives of the conference are to convene, connect, and engage diverse participants to make connections, build partnerships, and work collaboratively toward solutions. The conference will be held from January 5–9, 2021 in partnership with Project Drawdown and will encourage cross-disciplinary and innovative discussions about the changing conditions and interactions of intensifying heat, water scarcity, and impaired water quality on a host of integrated systems, including food provisioning, food system security, and the global supply chain. The partnership with Project Drawdown enables the NCSE conference to mobilize science to explore: (a) the physical effects of climate change and how these are linked to social institutions; and (b) how implementing climate solutions produces positive co-benefits to society, the economy, and the planet.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": "687", "attributes": { "award_id": "2105652", "title": "RAPID: Collaborative Research: The Integrity of Mail Voting", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 1575, "first_name": "Lee", "last_name": "Walker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-01", "end_date": "2021-11-30", "award_amount": 10342, "principal_investigator": { "id": 1576, "first_name": "Lonna Rae", "last_name": "Atkeson", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 170, "ror": "https://ror.org/05fs6jp91", "name": "University of New Mexico", "address": "", "city": "", "state": "NM", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 170, "ror": "https://ror.org/05fs6jp91", "name": "University of New Mexico", "address": "", "city": "", "state": "NM", "zip": "", "country": "United States", "approved": true }, "abstract": "Given the increase use of vote by mail (VBM) due to the COVID-19 pandemic, the investigators focus on mail-in voters' experience with how they seek, obtain, complete, return and have their mail ballots counted. They examine citizens' perceptions about the integrity of elections using VBM by assessing concerns about variation in the institutional structures of VBM, the secrecy of VBM the process, and the coercion that VBM voters may face from their peer group. The investigators use a state-centric survey design that includes an oversample in 10 states that have a mixture of VBM systems. The oversample is important and gives additional statistical power and leverage about state election administration and laws. The sample consist of only registered voters who report voting by mail in the 2020 election. Surveys are solicited online using Qualtrics software. E-mail addresses for registered voters by state will be purchased from L2. The investigators completed 200 online surveys with mail voters in 40 states, and 1,000 with mail voters in 10 states, along with 100 in-person voters in each these states, for a total sample of 23,000. This research provides a baseline for concerns about voter integrity related to mail balloting. Furthermore, it establishes whether alternative mail voting systems differ in terms of when, where, and with whom mail ballots are completed and returned. This project should inform scholars and policy makers in several areas of VBM policy administration. Findings from the study are also valuable in increasing public confidence in VBM election procedures. The research involves undergraduate researchers at all three campuses of the collaborative study.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": "686", "attributes": { "award_id": "2105682", "title": "RAPID: Collaborative Research: The Integrity of Mail Voting", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 1573, "first_name": "Lee", "last_name": "Walker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-01", "end_date": "2022-11-30", "award_amount": 5000, "principal_investigator": { "id": 1574, "first_name": "M V", "last_name": "Hood", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 160, "ror": "", "name": "University of Georgia Research Foundation Inc", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true } ] }, "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": "Given the increase use of vote by mail (VBM) due to the COVID-19 pandemic, the investigators focus on mail-in voters' experience with how they seek, obtain, complete, return and have their mail ballots counted. They examine citizens' perceptions about the integrity of elections using VBM by assessing concerns about variation in the institutional structures of VBM, the secrecy of VBM the process, and the coercion that VBM voters may face from their peer group. The investigators use a state-centric survey design that includes an oversample in 10 states that have a mixture of VBM systems. The oversample is important and gives additional statistical power and leverage about state election administration and laws. The sample consist of only registered voters who report voting by mail in the 2020 election. Surveys are solicited online using Qualtrics software. E-mail addresses for registered voters by state will be purchased from L2. The investigators completed 200 online surveys with mail voters in 40 states, and 1,000 with mail voters in 10 states, along with 100 in-person voters in each these states, for a total sample of 23,000. This research provides a baseline for concerns about voter integrity related to mail balloting. Furthermore, it establishes whether alternative mail voting systems differ in terms of when, where, and with whom mail ballots are completed and returned. This project should inform scholars and policy makers in several areas of VBM policy administration. Findings from the study are also valuable in increasing public confidence in VBM election procedures. The research involves undergraduate researchers at all three campuses of the collaborative study.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": "685", "attributes": { "award_id": "2035186", "title": "SBIR Phase I: STELLA – SATCOM TECHNOLOGY OF ELABORATE LUNEBURG LENS ANTENNA", "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": 1571, "first_name": "Muralidharan", "last_name": "Nair", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-15", "end_date": "2022-02-28", "award_amount": 276000, "principal_investigator": { "id": 1572, "first_name": "Patrick K", "last_name": "Gbele", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 363, "ror": "", "name": "US AIR TECH, LLC", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 363, "ror": "", "name": "US AIR TECH, LLC", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project include a high performance, low cos, dependable, novel antenna with high data bandwidth in 1000s of Gb (Tb) and high data rate speeds in 1000s of Gb/s (Tb/s). The elevated performance of this antenna, the cost effectiveness due to its 3D rapid prototype printing fabrication, and the easy integration to existing technologies may promote proliferation of wireless communications. The antenna may enable global connectivity and increase access to internet/phone connectivity for previously inaccessible areas of the globe, especially to disadvantaged and underserved communities. The high data bandwidth and speed rates will positively impact the scientific community and technologies based on data transfer such as remote learning, remote healthcare (remote surgery, patient consultation), the defense industry, telework (work from home during this COVID-19 pandemic), etc. The antenna’s technical superiority and low cost support substantial anticipated commercial success.This Small Business Innovation Research (SBIR) Phase I project addresses critical challenges in the two emerging wireless communications systems: LEO-SATCOM (Low Earth Orbit – Satellite Communications) and 5G mobile phone/internet. This project will develop a unique antenna technology that will be integrated into satellite gateways, 5G ground terminals and also satellites in orbit. The wide aperture angle of the antenna provides a wide scanning angle capability that enables connection to highly inclined satellites. The antenna is also capable of multi-beam analysis to enable the simultaneous tracking of multiple satellites and to insure no down time during handoffs. The radiation beam pattern has excellent characteristics of high gain (Equivalent Isotropic Radiated Power), very narrow beamwidth, and low cross polarization.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": "684", "attributes": { "award_id": "2046259", "title": "CAREER: Mechanical and Structural Adaptations of Blood Vessels in Pulmonary Arterial Hypertension", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 1569, "first_name": "Lucy T.", "last_name": "Zhang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2026-02-28", "award_amount": 551341, "principal_investigator": { "id": 1570, "first_name": "Daniela", "last_name": "Valdez-Jasso", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 258, "ror": "", "name": "University of California-San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 258, "ror": "", "name": "University of California-San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "This Faculty Early Career Development (CAREER) award will focus on better understanding the adverse changes that occur in the arteries of the lung during pulmonary arterial hypertension. This high blood pressure in the pulmonary arteries has a high mortality rate; the only cure is a lung transplant. COVID-19 may also increase the risk of developing this chronic disease. Previous work has shown that accumulation of fibrous tissue in the arteries during disease progression is accompanied by an increase in their mechanical stiffness, which impairs lung blood flow. The specialized cells that synthesize the fibrous matrix of the pulmonary arteries are thought to be stimulated by changes in their mechanical environment. However, the biological mechanisms by which the diseased arteries respond to increased blood pressure and how the structural changes in the vessel wall affect their mechanical properties remain poorly understood. This work will use novel bioengineering measurements and mathematical analysis to improve understanding of the mechanics of disease progression and identify new therapeutic targets. The integration of mathematics, engineering, and biology in this research will also be applicable to other diseases. This research will be complemented with an outreach program that teaches students how skills in biology, mathematics and engineering can be combined to discover solutions to chronic health problems. Undergraduate students will gain hands-on access to the laboratory facilities used in this research.This research will test the hypothesis that the dynamic changes in pulmonary arterial wall mechanics and extracellular matrix stiffness during pulmonary arterial hypertension impair hemodynamics and regulate adventitial matrix remodeling and stiffening via interactions between profibrotic mechano-signaling pathways. A multiscale approach to this research will integrate experimental and modeling studies by (1) measuring and modeling the time courses of changes in pulmonary arterial hemodynamics, morphology and physiology in vivo in a rat model of the disease; (2) measuring the nonlinear biaxial mechanical properties and structure of arterial tissue and collagen matrix during disease remodeling and use microstructural constitutive models to relate these structural changes to vascular stiffness; and (3) measuring how changes in vessel strain and structural properties regulate profibrotic phenotypes and gene expression and predict them with a mathematical model of the cell regulatory 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 } } ], "meta": { "pagination": { "page": 1383, "pages": 1424, "count": 14236 } } }