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The purpose of this Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is to encourage applications that will develop and validate novel tools to facilitate the detailed analysis of complex circuits and provide insights into cellular interactions that underlie brain function. The new tools and technologies should inform and/or exploit cell-type and/or circuit-level specificity. Plans for validating the utility of the tool/technology will be an essential feature of a successful application. The development of new genetic and non-genetic tools for delivering genes, proteins and chemicals to cells of interest or approaches that are expected to target specific cell types and/or circuits in the nervous system with greater precision and sensitivity than currently established methods are encouraged. Tools that can be used in a number of species / model organisms rather than those restricted to a single species are highly desired. Applications that provide approaches that break through existing technical barriers to substantially improve current capabilities are highly encouraged.

The purpose of this Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is to encourage applications that will develop and validate novel tools to facilitate the detailed analysis of complex circuits and provide insights into cellular interactions that underlie brain function. The new tools and technologies should inform and/or exploit cell-type and/or circuit-level specificity. Plans for validating the utility of the tool/technology will be an essential feature of a successful application. The development of new genetic and non-genetic tools for delivering genes, proteins and chemicals to cells of interest or approaches that are expected to target specific cell types and/or circuits in the nervous system with greater precision and sensitivity than currently established methods are encouraged. Tools that can be used in a number of species / model organisms rather than those restricted to a single species are highly desired. Applications that provide approaches that break through existing technical barriers to substantially improve current capabilities are highly encouraged.

The functionality of the NeuroImaging Tools and Resources Collaboratory (NITRC) has enabled three distinct components to flourish: Resources Registry (NITRC-R): a collaboratory enabling the distribution, enhancement, and adoption of neuroimaging tools and resources. Image Repository (NITRC-IR): a curated repository of free neuroimaging datasets meeting global standards. Computational Environment (NITRC-CE): a freely downloadable or pay-as-you-go virtual computing cloud-based platform that is pre-configured with popular neuroimaging tools. NITRC-R has become the major web-based collaborative environment enabling the distribution, enhancement, and adoption of neuroinformatics resources. It currently hosts more than 1,000 tools and resources in areas such as magnetic resonance imaging (MRI), computed tomography (CT), optical imaging, positron emission tomography/single-photon emission computed tomography (PET/SPECT), electroencephalography/magnetoencephalography/electrocorticography (EEG/MEG/ECoG), computational neuroscience, and imaging genomics. Since NITRC's inception, there have been more than 10 million total downloads of tools from NITRC-R.

The Transformational Tools and Technologies (TTT) Project advances state-of-the-art computational and experimental tools and technologies that are vital to aviation applications in the six strategic thrusts. The project develops new computer-based tools, computational fluid dynamics models, and associated scientific knowledge that will provide first-of-a-kind capabilities to analyze, understand, and predict aviation concept performance. These revolutionary tools will be applied to accelerate NASA's research and the community's design and introduction of advanced concepts. The Project also explores technologies that are broadly critical to advancing ARMD strategic outcomes. Such technologies include the understanding of new types of strong and lightweight materials, innovative controls techniques, and experimental methods. The TTT Materials and Structures Discipline emphasizes improved multifunctional and high temperature materials for airframe and engine application, as well as integrated multiscale modeling and simulation tool development to improve validated first-principles materials and structural modeling.

The purpose of this Funding Opportunity Announcement [FOA] submitted through the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is to stimulate the development and validation of novel tools and analytical methods to target, identify and characterize non-neuronal cells in the brain. This FOA complements previous and ongoing cell-census and tool development efforts initiated under BRAIN, RFA-MH-14-215 and RFA-MH-14-216, that have focused almost exclusively on neuronal cells. The cutting-edge tools and methods developed under this opportunity should focus specifically on providing improved points of entry into non-neuronal cell-types (glial and vascular) to enable their inventory and characterization within the CNS and help define how these cells interact among each other and with neuronal cells to impact functional circuitries. Plans for validating the utility of the tool/technology/method and demonstrating its advantage over currently available approaches will be an essential feature of a successful application. Tools that can be used in several species or model organisms rather than in a single species are especially desirable.

This FOA solicits development of innovative adaptations of existing technologies to enable their use for readily identifying, manipulating, or analyzing glycans and their biological binding partners. This may encompass the adaptation of commonly used laboratory-based or computational tools to enable their facile application to glycoscience for the first time, as well as the adaptation of tools presently used by specialists in glycoscience to make them significantly more straightforward and accessible for non-specialists. It is possible that a project might simplify a current specialized approach by migrating it to a more commonly used platform, developing automation for data acquisition and interpretation, or redesigning the present tool to make it easier to use. This announcement differs from the related FOA RFA- RM-16-022 which solicits new or more effective tools or technologies, thus representing an expansion of existing technologies.

This FOA solicits new theories, computational models, and statistical tools to derive understanding of brain function from complex neuroscience data. Proposed tools could include the creation of new theories, ideas, and conceptual frameworks to organize/unify data and infer general principles of brain function; new computational models to develop testable hypotheses and design/drive experiments; and new mathematical and statistical methods to support or refute a stated hypothesis about brain function, and/or assist in detecting dynamical features and patterns in complex brain data. It is expected that the tools developed under this FOA will be made widely available to the neuroscience research community for their use and modification. Investigative studies should be limited to validity testing of the tools being developed.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

The Common Fund Program - Accelerating Translation of Glycoscience: Integration and Accessibility - aims to develop accessible and affordable new tools and technologies for studying carbohydrates that will allow biomedical researchers to significantly advance our understanding of the roles of these complex molecules in health and disease. This program will enable investigators who might not otherwise conduct research in the glycosciences, to undertake the study of carbohydrate structure and function. In support of these aims, this FOA seeks applications for a community-driven project to develop computational and informatics tools for the manipulation, analysis, interpretation, and integration of glycoscience data. The product of this research will be accessible resources for analysis of carbohydrate and glycoconjugate structural, analytical, and interaction data, and integration of that information within the context of comparable gene, protein, and lipid data and databases.

This Funding Opportunity Announcement (FOA) intends to accelerate the integration and use of scalable technologies and tools to enhance brain cell census research, including the development of technology platforms and/or resources that will enable a swift and comprehensive survey of brain cell types and circuits. Applications are expected to address limitations and gaps of existing technologies/tools as a benchmark against which the improvements or competitive advantages of the proposed ones will be measured.

This Funding Opportunity Announcement (FOA) intends to accelerate the integration and use of scalable technologies and tools to enhance and reinvigorate brain cell census research, including the development of technology platforms and/or resources that will enable a swift and comprehensive survey of brain cell types and circuits. Of particular interest are those that will (a) improve technology and resource platforms to remove limitations and bottlenecks in the current pipeline of brain cell census data generation; (b) integrate experimental and computational methods to enhance capabilities of cell census data generation and analysis and to reduce barriers to hypothesis-driven research; (c) generate a substantial amount of spatiotemporal cell census data and/or resources to demonstrate the utility of the improved technology and resource platforms; and (d) conduct comparative studies by using proper criteria to evaluate and benchmark quality of biospecimen, performance of cell census tools/technologies, and effectiveness of computational approaches. The projects funded under this FOA will align with the overarching goals of the BRAIN Initiative Cell Census Network (BICCN) and are expected to generate a substantial amount of cell census data using the proposed technologies or via collaboration with the BICCN.

The purpose of this FOA is to support a more efficient method for jurisdictions to de-duplicate the National HIV Surveillance System. The applicant will develop a privacy data-sharing tool capable of identifying potential duplicates across jurisdictions. Activities will include acquiring a Security Assessment and Authorization, negotiating with the 59 jurisdictions to obtain their participation, providing a data sharing tool that will allow for secure, encrypted submission and matching of person-level HIV surveillance data, and providing a report back to jurisdictions on matching levels.

Weigh-in-motion (WIM) systems are a vital means for collecting traffic data-critical input for pavement and bridge designs-used for making transportation and freight planning decisions and in highway safety investigations. There are, however, many potential sources of error in WIM measurements which make it difficult for data collectors to evaluate data accuracy and consistency. For over a decade, the Federal Highway Administration (FHWA) Long-Term Pavement Performance (LTPP) program collected a massive amount of WIM data, along with information about the performance of WIM equipment. This includes the WIM validation and calibration data from 24 LTPP Specific Pavement Studies (SPS) test sites across North America. This and other data sets provide an opportunity to develop more advanced WIM tools to help state highway practitioners perform WIM site selection, sensor selection, maintenance, development of calibration procedures including frequency, and data quality acceptance. These tools could help improve WIM data accuracy and consistency by considering factors such as temperature and seasonal effects, vehicle speed, pavement condition, changes in truck population and configurations, data sampling frequencies, system age, and other factors.

The Federal Highway Administration (FHWA) and the American Association of State Highway Transportation Officials (AASHTO) have adopted its use and translated the variables into civil engineering applications, specifically pavement design. FHWA's Long Term Pavement Performance (LTPP) Climate Tool provides access to the MERRA-2 database and generates site-specific climate data in compatible formats for AASHTO Pavement ME Design (Pavement ME). AASHTO will soon use MERRA-2 climatic data for AASHTOWare applications. MERRA-2 data sets include accurate hourly solar radiation values based on measured cloud-covered fractions which can significantly improve the accuracy of predicted pavement temperatures. Studies reveal challenges in matching the predictions from the Enhanced Integrated Climatic Model (EICM) with field observations and pavement performance. Variations in measurement of climatic attributes have also been reported to Operating Weather Stations (OWS). MERRA-2 data provides opportunities for enhancements to the climatic parameters and climatic module calculations for pavement design using Pavement ME. It provides improved climatology, higher frequency outputs including hourly data updates, and additional locations beyond the United States. Available data categories include: temperature, precipitation, surface pressure, cloud cover, humidity, wind speed, and solar radiation. The objectives of this project are to (1) evaluate the impact of using NASA's Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) through the FHWA LTPP Climate Tool to improve the climatic inputs and related models for Pavement ME; (2) enhance and simplify climate input parameters for Pavement ME that can be implemented by transportation agencies; and (3) develop climate-related models based on identified parameter enhancements

The purpose of this funding opportunity announcement (FOA) is to support the development of novel tools and technologies through the Small Business Innovation Research (SBIR) program to advance the field of neuroscience research. This FOA specifically supports the development of novel neurotechnologies as well as the translation of technologies developed through the BRAIN initiative or through other funding programs, towards commercialization. Funding can support the iterative refinement of these tools and technologies with the end-user community, with an end-goal of scaling manufacture towards reliable, broad, sustainable dissemination and incorporation into regular neuroscience research.

The purpose of this funding opportunity announcement (FOA) is to support the development of novel tools and technologies through the Small Business Technology Transfer (STTR) program to advance the field of neuroscience research. This FOA specifically supports the development of novel neurotechnologies as well as the translation of technologies developed through the BRAIN initiative or through other funding programs, towards commercialization. Funding can support the iterative refinement of these tools and technologies with the end-user community, with an end-goal of scaling manufacture towards reliable, broad, sustainable dissemination and incorporation into regular neuroscience practice.

This Funding Opportunity Announcement (FOA) intends to accelerate the use of scalable technologies and tools to enhance brain cell census research, including the development of technology platforms and/or resources and the generation of spatiotemporal cell census data and/or resources. Applications are expected to address limitations and gaps of existing technologies/tools as a benchmark against which the improvements or competitive advantages of the proposed ones will be measured. The improvements include throughput, sensitivity, selectivity, scalability, spatiotemporal resolution and reproducibility in cell atlas analyses. The projects funded under this FOA will align with the overarching goals of the BRAIN Initiative Cell Census Network (BICCN) and are expected to enable the generation of a large amount of cell census data using the proposed technologies or via collaboration with the BICCN.

The Engineering and Systems Design (ESD) program supports research leading to design theory and to tools and methods that enable implementation of the principles of design theory in the practice of design across the full spectrum of engineered products and systems. The program focus is on gaining an understanding of the basic processes and phenomena underlying a holistic, life-cycle view of design where the total system life-cycle context recognizes the need for advanced understanding of the identification and definition of preferences, analysis of alternatives, effective accommodation of uncertainty in decision-making, and the relationship between data and knowledge in a digitally-supported process and environment. The program funds advances in basic design theory, tools, and software to implement design theory and new design methods that span multiple domains, such as design for the environment, for manufacturability, and for systems. 28 28

This Funding Opportunity Announcement (FOA) seeks clinical research focused on the development and utilization of technologies that can help address patient outcomes. Relevant areas of technology include remote healthcare delivery to patients via telehealth, robotics to enhance medication adherence, on-site (e.g., clinical or home setting) care delivery, mobile heath to increase access and adherence, web-based decision support tools, and others.  Research projects may focus on assessment, diagnosis, intervention development, or intervention implementation.  Research projects that a) incorporate emerging and cutting edge technologies to explain and predict patient trajectories, b) inform interventions, c) support real-time clinical decision making, and d) facilitate effective long-term management of chronic illness are especially needed.  Critical to this FOA, proposed research should identify specific patient outcomes expected to improve from technological approaches.  The specific tools or interventions proposed should clearly indicate how they will enhance patient benefits in environments, such as clinical settings, and/or in the home and community.

This Funding Opportunity Announcement (FOA) encourages bioengineering applications that will accelerate the development and adoption of promising tools and technologies that can address important biomedical research problems. The objectives are to establish these tools and technologies as robust, well-characterized solutions that fulfill an unmet need and are capable of enhancing our understanding of life science processes or the practice of medicine. Awards will focus on supporting multidisciplinary teams that apply an integrative, quantitative bioengineering approach to developing these technologies and engage biomedical researchers or clinicians throughout the project. The goal of the program is to support projects that can realize meaningful solutions within 5-10 years.