Category Archives: Applied Science and Technology

2020 Preservation Technology and Training Grants

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The U.S. Department of the Interior – National Park Service 2020 Preservation Technology and Training Grants (PTT) are intended to create better tools, better materials, and better approaches to conserving buildings, landscapes, sites, and collections. PTT are administered by the National Center for Preservation Technology and Training – NCPTT, the National Park Service’s innovation center for the preservation community. The competitive grants program will provide funding to federal agencies, states, tribes, local governments, and non-profit organizations. PTT Grants will support the following activities:

  • Innovative research that develops new technologies or adapts existing technologies to preserve cultural resources – typically 20,000 dollars.
  • Specialized workshops or symposia that identify and address national preservation needs – typically 15,000 to 20,000 dollars.
  • How-to videos, mobile applications, podcasts, best practices publications, or webinars that disseminate practical preservation methods or provide better tools for preservation practice – typically 5,000 to 15,000 dollars.

The maximum grant award is 20,000 dollars. The actual grant award amount is dependent on the scope of the proposed activity. NCPTT does not fund brick and mortar grants.

If you have difficulty accessing the full announcement electronically, please contact Todd Wilson.

FY2021 Defense University Instrumentation Program (DURIP)

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This announcement seeks proposals from universities to purchase equipment and instrumentation in support of research in areas of interest to the Department of Defense.

DoD interests include the areas of research supported by the Army Research Office (ARO), the Office of Naval Research (ONR), and the Air Force Office of Scientific Research (AFOSR), hereafter generally referred to collectively as “we,” “our,” “us,” or “administering agency.” We use “administering agency” to provide a generic reference to any of the administering agencies.

A central purpose of the DURIP is to provide equipment and instrumentation to enhance research related education in areas of interest and priority to the DoD. Therefore, your proposal must address the impact of the equipment or instrumentation on your institution’s ability to educate students through research in disciplines important to DoD missions.

ADMINISTERING AGENCY – HOW TO FIND RESEARCH INTERESTS

Army Research Office (ARO)

Navigate to the “Broad Agency Announcements” section to see the most recent ARL or ARO Core Broad Agency Announcement for Basic and Applied Scientific Research.

Office of Naval Research (ONR)

Select “Work With Us” and then “Funding Opportunities” to see the Long Range Broad Agency Announcement for Navy and Marine Corps Science and Technology, BAA N00014-20-S-B001.

Air Force Office of Scientific Research (AFOSR)

Navigate to https://www.grants.gov/web/grants/view-opportunity.html?oppId=314753 to view the “Research Interests of the Air Force Office of Scientific Research,” BAA FA9550-19-S-0003.

You must refer to the websites cited above for detailed technical information and the technical goals. DoD encourages you to contact the Program Managers listed in the cited announcements before submitting proposals to explore research areas of mutual interest to you and us.

You may submit a single DURIP proposal to more than one administering agency; however, only one administering agency will fund it, if selected. There is no limit on the total number of different proposals you can submit. There is no limit to the number of awards a single applicant organization can receive under this competition. DoD discusses this again in sections C.3.b Amount of Requested DoD Funding and D.4.g Submission to Multiple Administering Agencies.

DoD reserves the right to select and fund for award, all, some, part, or none of the proposals received. There is no guarantee of award.

Notice of Special Interest (NOSI) to Highlight Research Priorities for Risk Algorithms Applications in Healthcare Settings to Improve Suicide Prevention

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Notice Number: NOT-MH-20-031

Key Dates
Release Date: February 14, 2020
First Available Due Date: June 05, 2020
Expiration Date: January 08, 2022 Related Announcements
PAR-19-189, Pilot Services Research Grants Not Involving Clinical Trials (R34 Clinical Trial Not Allowed)

PAR-17-264, Innovative Mental Health Services Research Not Involving Clinical Trials (R01)

PA-19-056, NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)

PA-19-055, Research Project Grant (Parent R01 Clinical Trial Required)

PA-18-350, NIMH Exploratory/Developmental Research Grant (R21 Clinical Trial Not Allowed)

PA-19-052, NIH Small Research Grant Program (Parent R03 Clinical Trial Not Allowed)

RFA-MH-18-700, Clinical Trials to Test the Effectiveness of Treatment, Preventive, and Services Interventions (Collaborative R01 – Clinical Trial Required)

RFA-MH-18-701, Clinical Trials to Test the Effectiveness of Treatment, Preventive, and Services Interventions (R01 Clinical Trial Required)

RFA-MH-18-706, Pilot Effectiveness Trials for Treatment, Preventive and Services Interventions (R34- Clinical Trial Required)

PAR-18-929, High-Priority Areas for Research Leveraging EHR and Large-Scale Data (R01 Clinical Trial Not Allowed)

PA-18-566 Complex Technologies and Therapeutics Development for Mental Health Research and Practice (R43/R44 Clinical Trial Optional)

Issued by National Institute of Mental Health (NIMH)

Purpose

Risk identification is a key component of suicide prevention. In healthcare settings, current risk identification is typically obtained through patients’ endorsement of items on screeners, either administered by a clinician or completed by patients through a tablet or via paper/pencil. Another way to identify people with suicide risk is via risk algorithms based on medical record data, which can be considered complementary to the traditional screening associated with clinical encounters in several ways: 1) it does not rely on people to answer questions, it looks at what they have done as opposed to what they say; 2) you can look across a panel of people – not just those seen in face-to-face healthcare contacts.

Risk algorithms have been shown in multiple settings to be a validated way to identify individuals with high suicide risk who warrant additional clinical attention. To date, risk algorithm approaches have not been designed to predict outcomes for individual patients, but rather to assign people into differential tiers of risk. The use of these tools presents some special challenges, including issues around logistics, ethics, and acceptability, and each of these areas present research gaps.

NIMH held a meeting in June 2019 to identify and prioritize research needs in the application of predictive analytics in suicide prevention among healthcare providers. The meeting summary details research topics and gaps that included: biostatistical challenges, provider and patient understanding of risk algorithms, ethical considerations, needs for clinical decision tools to guide risk algorithm application, and policy-relevant research. NIMH is encouraging practice and deployment relevant applications proposed by multidisciplinary teams addressing the following topics:

Biostatistical Challenges:

  • Test approaches that could lead to:
    • Identifying best practices in the design of the cohorts used to develop risk algorithms, to ensure that the design is suitable for the purpose(s) for which the algorithm is being utilized.
    • Identifying best practices in assessing the performance of suicide risk algorithms – including possible effects on equity in treatment and outcomes.
  • Examine the benefits and limitations of risk algorithms that consider multiple or composite outcomes, such as risk for non-fatal as well as fatal suicide events, fatal and non-fatal accidents, and others.
  • Examine the benefits and limitations of developing and operating multiple risk algorithms for specific subgroups within a larger population/cohort (e.g., those with certain characteristics or experiences, or in certain geographic or care settings), versus one algorithm that is used with the entire population/cohort.
  • Develop and test criteria to determine when it might be appropriate to use an algorithm developed in one setting or population/cohort and apply it in a different setting or population/cohort (e.g. if health system B uses an algorithm developed and validated by health system A); versus developing and validating algorithms for each specific setting or population/cohort that seeks to use this approach.
  • Compare risk modeling benefits and challenges over alternative time periods, e.g., outcomes within 1 vs. 3 vs. 12 months. For example, if long time periods take place between algorithm calculations, at what point are the outcomes ‘stale’ and less clinically useful?
  • Explore whether risk algorithms preserve or – worse – potentially expand disparities in treatment and outcomes; and, if so, develop possible methods to mitigate this.
  • What are special considerations for developing risk algorithms for smaller subgroups (e.g., historically disadvantaged groups, sexual minorities, age groups, etc.), such as longer time frames needed and prediction utility?
  • Examine the relationships between absolute (predicted) risk, on the one hand, and how identified patients may respond to intervention, on the other. Assess the potential added value of drawing on various types of data in developing risk algorithms, e.g., structured measures from health care claims/encounters and electronic health records, patient-reported measures, measures derived via abstraction or natural language processing from patient care records, measures derived from passive sensor monitoring (e.g., via smartphone); as well as the value of data derived from outside healthcare (e.g., social media, public records, and commercially available data such as credit information, among others).

Provider Understanding, Acceptance and Use of Results from Suicide Risk Algorithms:

  • What clinical decision-making data and practical approaches facilitate deciding which risk model to use; what risk strata to intervene on, and how to intervene?
  • How could information on potential patient responses to targeted clinical interventions affect how risk algorithm models are developed, and how they are used (e.g., will patients engage in the interventions offered; what are rates of response to the intervention)?
  • What are useful approaches to determining when a risk indicator be ‘turned off’ (e.g., indicators of ‘recovery’)

Patient Understanding and Acceptance of Results from Suicide Risk Algorithms, and Ethical Concerns (see also NOT-OD-20-038)

Research is needed that tests approaches to educating patients about risk categories and how clinical care and personal actions may change risk status, with implications for developing healthcare setting best practices in applying risk algorithms to care. When and how are informed consent processes needed when using suicide risk algorithms in practice? Should risk algorithm outcomes be considered PHI for purposed of HIPAA? Practically, how would risk algorithm outcomes be provided in patient portal access (e.g., as a test result with interpretation)? How can patients’ family members/designated significant others, be informed of a patients’ increased risk? Under what circumstances do patients see algorithm use as ‘intrusive,’ or inaccurate (where they may be perpetuating disparities in healthcare services), and what are potential remedies to address these problems?

All requirements of the relevant FOA would need to be followed in any application (and award) that proposes to develop and conduct a study on one of these high priority areas. Possible funding opportunities that can be used to pursue these and other research activities include the following FOAs and any re-issuances of these FOAs through the expiration date of this notice. Please note that investigators interested in pursuing clinical trial research should review the NIMH Clinical Trials Funding Opportunity Announcements Website.

Investigators seeking National Death Index Linkage should review NOT-OD-20-057, National Death Index Linkage Access for NIH-Supported Investigators.

Applicants considering such an application are strongly encouraged to consult with NIMH Program Officials prior to submission.

Application and Submission Information

This notice applies to due dates on or after June 5, 2020 and subsequent receipt dates through September 8, 2022.

Submit applications for this initiative using one of the following funding opportunity announcements (FOAs) or any reissues of these announcement through the expiration date of this notice.

R34 – PAR-19-189, Pilot Services Research Grants Not Involving Clinical Trials (R34-Clinical Trial Not Allowed) – First Available Due Date 06/16/2020

R01 – PAR-17-264, Innovative Mental Health Services Research Not Involving Clinical Trials (R01) – First Available Due Date 06/05/2020

R01 – PAR-18-929, High-Priority Areas for Research Leveraging EHR and Large-Scale Data (R01-Clinical Trial Not Allowed) – First Available Due Date 06/05/2020

R01 – PA-19-056, NIH Research Project Grant (Parent R01-Clinical Trial Not Allowed) – First Available Due Date 06/05/2020

R01 – PA-19-055, Research Project Grant (Parent R01-Clinical Trial Required) – First Available Due Date 06/05/2020

R21 – PA-18-350, NIMH Exploratory/Developmental Research Grant (R21-Clinical Trial Not Allowed) – First Available Due Date 06/16/2020

R03 – PA-19-052, NIH Small Research Grant Program (Parent R03- Clinical Trial Not Allowed) – First Available Due Date 06/16/2020

R34 – RFA-MH-18-706, Pilot Effectiveness Trials for Treatment, Preventive and Services Interventions (R34-Clinical Trial Required) – First Available Due Date 06/15/2020

R01 – RFA-MH-18-701, Clinical Trials to Test the Effectiveness of Treatment, Preventive, & Services Interventions (R01-Clinical Trial Required) – First Available Due Date 06/15/2020

R01 – RFA-MH-18-700, Clinical Trials to Test the Effectiveness of Treatment, Preventive, & Services Interventions (Collaborative R01-Clinical Trial Required) – First Available Due Date 06/15/2020

All instructions in the SF424 (R&R) Application Guide and the funding opportunity announcement used for submission must be followed, with the following additions:

  • For funding consideration, applicants must include “NOT-MH-20-031” (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.

Applications non-responsive to terms of this NOSI will be not be considered for the NOSI initiative.

Measurement Science and Engineering (MSE) Research Grant Programs

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The Department of Commerce’s National Institute of Standards and Technology (NIST) is soliciting applications for financial assistance for Fiscal Year 2020 (FY20) within the Office of the Associate Director for Innovation and Industry Services (ADIIS).

Program Description: The ADIIS Grant Program supports activities that develop, expand, strengthen, or sustain NIST partnership programs within the ADIIS Directorate through measurements, standards, data, industry and technology studies, and technology research and development (R&D). Specifically, the ADIIS Grant Program seeks to support technology innovation and service to American industry in the following fields: bioscience, chemistry, dimensional metrology, electronics, engineering, infrastructure, information technology, manufacturing, manufacturing metrology, materials science and engineering, nanotechnology, neutron research, optics, and physics.

The ADIIS Directorate’s current partnership programs include the Baldrige Performance Excellence Program, the Hollings Manufacturing Extension Partnership (MEP), programs within the NIST Office of Advanced Manufacturing, and programs within the NIST Technology Partnerships Office. Financial assistance may be provided to bolster measurements, standards, data and technology R&D within these partnership programs, or through new partnerships, to:

  • Advance early-stage research and development for industry
  • Enhance opportunities in manufacturing through innovation
  • Strengthen supplier programs for small and medium manufacturers
  • Encourage the transfer and commercialization of research and technology from institutions of higher education, federal laboratories, other federally funded research programs, and nonprofit research institutes
  • Create jobs or promote workforce development
  • Realize or sustain metrology needs in American industry, including through technical metrology training programs for manufacturers

Eligibility for all programs listed in this Notice of Funding Opportunity (NOFO) includes all non-Federal entities, including institutions of higher education, non-profit organizations, for-profit organizations, state and local governments, Indian tribes, hospitals, foreign public entities, and foreign governments. Please note that individuals and unincorporated sole proprietors are not considered “non-Federal entities” and are not eligible to apply under this NOFO. The NOFO’s full text can be found here and downloaded as a PDF or a zip file.

National Science Foundation: Salary & Wages Policy

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The NSF recently released the PAPPG 20-1, which applies to proposals submitted or due, or awards made, on or after June 1, 2020. Section IIC2g(i) includes the following language for Senior Personnel & Wages:

“NSF regards research as one of the normal functions of faculty members at institutions of higher education. Compensation for time normally spent on research within the term of appointment is deemed to be included within the faculty member’s regular organizational salary.”

“As a general policy, NSF limits the salary compensation requested in the proposal budget for senior personnel to no more than two months of their regular salary in any one year. (See Exhibit II-3 for the definitions of Senior Personnel.) It is the organization’s responsibility to define and consistently apply the term “year”, and to specify this definition in the budget justification. This limit includes salary compensation received from all NSF-funded grants. This effort must be documented in accordance with 2 CFR § 200, Subpart E, including 2 CFR § 200.430(i). If anticipated, any compensation for such personnel in excess of two months must be disclosed in the proposal budget, justified in the budget justification, and must be specifically approved by NSF in the award notice budget.16“

Please note that any proposals submitted or due, or awards made, prior to June 1, 2020 will still be subject to the policies and procedures established in the PAPPG 19-1.