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The purpose of this Funding Opportunity Announcement is to seek cost-shared projects for the research of medium and heavy-duty on-road natural gas engines. Specifically, this topic addresses engine efficiency improvements, fuel system enhancements, and emission after-treatment technologies, which are barriers to the adoption of natural gas engine technologies. Information on where to submit questions regarding the content of the announcement and where to submit questions regarding submission of applications is found in the full FOA posted on the EERE Exchange website.

The U.S. Department of Energy?s Office of Electricity Delivery and Energy Reliability, in collaboration with the U.S. Department of Homeland Security?s Science and Technology Directorate and Energy Sector Control Systems Working Group (ESCSWG) in support of the Electricity Sub-sector Coordinating Council, Oil and Natural Gas Sector Coordinating Council, and the Government Coordinating Council for Energy under the Critical Infrastructure Partnership Advisory Council (CIPAC) Framework, facilitated the development of the Roadmap to Achieve Energy Delivery Systems Cybersecurity . The Roadmap synthesizes expert input from the energy delivery control systems community, including owners and operators, commercial vendors, national laboratories, industry associations, and government agencies. The Roadmap presents a strategic framework supported by key milestones that must be met to achieve the Roadmap vision that by 2020 resilient energy delivery sys tems are designed, installed, operated and maintained to survive a cyber-incident while sustaining critical functions. This announcement focuses on providing tools and technologies research, development and demonstration to support the Cybersecurity for Energy Delivery Systems Program (CEDS) within the Power Systems Engineering Research and Development (PSE R&D) Division of the Office of Electricity Delivery and Energy Reliability (OE). The CEDS program has established partnerships over the past several years throughout the energy sector, government, national laboratories and universities to reduce the risk of energy delivery disruption resulting from a cyber event. The CEDS program desires to advance research, development and demonstration of tools and technologies that align with the strategic framework of the energy sector?s Roadmap, address Roadmap milestones and work toward achieving the Roadmap vision.

The HPEM Modeling & Effects research and development effort consists of the following areas: understanding the connectivity of infrastructure and mobile targets; understanding the phenomenology of front door effects; developing a predictive effects model; developing a theoretical and empirical basis for HPEM effects ranging from the basic circuit level to the system level effects; empirical effects testing on operational targets as a function of frequency, pulsed duration, and power of the incident HPEM pulse; battle damage assessment; rapid modeling of HPEM system sources and components; improving particle-in-cell code (PIC) capabilities; first principles materials modeling; improving models for electron emission, gas desorption to enhance the predictive capability of virtual prototyping; and developing electromagnetic (EM) algorithms to propagate radio frequency (RF) from platform-specific high power RF systems to targets to assess the performance measures of effective HPEM sources. Sound software engineering and development principles must be employed for all developed software and documentation. Robust software testing, validation, and verification are critical to software development efforts. As appropriate, software must scale to large simulation sizes and be portable to massively parallel computer architecture.

Pandemics have far reaching consequences that range from deaths to shutting down the economy as we have witnessed during the recent COVID19 crisis. Hence there is a need to be better prepared for such pandemics. We need to solve problems ranging from predictive analytics innovative devices for saving lives to technology for devising voting machines. The social and economic impact for the above areas is huge and some of the work can be transformative and save lives. Areas of interest to us include, but are not limited to: - Mathematical models for spread and the impact of pandemics. - Scalable simulation techniques for pandemics (e.g. with multi agents). - Biomedical/Nano sensor devices for detecting symptoms and agents. - Algorithms for rapid exploration of the drug screening and discovery workflows (e.g. use reinforcement learning) - Advanced computational biology techniques for sequencing, detecting viral evolution (e.g. in COVID-19). - Algorithms and systems for contact tracing (with privacy preserving). - Algorithms and recommendation systems for curating media and news. - Collaboration techniques for more effective health, and efficiency during pandemics. Improved identity and security techniques. - Distributed Ledgers, their applications and their governance for and during pandemics. - Pandemic data science - understanding the patterns and the impact of a pandemic like COVID-10. Creation of curated data sets. We are interested in both the science and technology aspects of these problem sets, and, particularly, in the intersections between them.

NSF-supported science and engineering research increasingly relies on cutting-edge infrastructure. With its Major Research Instrumentation (MRI) program and Major Multi-user Facilities (Major Facilities) projects, NSF supports infrastructure projects at the lower and higher ends of infrastructure scales across science and engineering research disciplines. The Mid-scale Research Infrastructure Big Idea is intended to provide NSF with an agile, Foundation-wide process to fund experimental research capabilities in the mid-scale range between the MRI and Major Facilities thresholds. NSF defines Research Infrastructure (RI) as any combination of facilities, equipment, instrumentation, or computational hardware or software, and the necessary human capital in support of the same. Major facilities and mid-scale projects are subsets of research infrastructure. The NSF Mid-scale Research Infrastructure-1 Program (Mid-scale RI-1) supports the design or implementation of unique and compelling RI projects. Mid-scale RI-1 implementation projects may include any combination of equipment, instrumentation, cyberinfrastructure, broadly used large-scale datasets, and the commissioning and/or personnel needed to successfully complete the project, or the design efforts intended to lead to eventual implementation of a mid-scale class project. Mid-scale RI-1 design projects will include the design efforts intended to lead to eventual implementation of a mid-scale class RI project. Mid-scale RI-1 projects should fill a research community-defined scientific need or enable a national research priority to be met. Mid-scale RI-projects should also enable US researchers to remain competitive in a global research environment and involve the training of a diverse workforce engaged in the design and implementation of STEM infrastructure.

NGA welcomes all innovative ideas for path-breaking research that may advance the GEOINT mission. The mission of the National Geospatial-Intelligence Agency (NGA) Research Directorate is to deliver future Geospatial-Intelligence (GEOINT) capabilities to users for operational impact. NGA Research supports the National Security Strategy by solving hard defense and intelligence problems for the Intelligence Community and Department of Defense. GEOINT is the exploitation and analysis of imagery and geospatial information to describe, assess, and visually depict physical features and geographically referenced activities on the Earth. GEOINT consists of imagery, imagery intelligence, and geospatial information. NGA offers a variety of critical GEOINT products in support of U.S. national security objectives and Federal disaster relief, including aeronautical, geodesy, hydrographic, imagery, geospatial and topographical information. The Boosting Innovative GEOINT-Research Broad Agency Announcement (BIG-R BAA) invites proposers to submit innovative basic and applied research and development concepts that address one or more of the following technical domains: (1) Foundational GEOINT, (2) Advanced Phenomenologies, and (3) Analytic Technologies. It is NGA's intent to solicit basic and applied research under this BAA. NGA seeks proposals from qualified proposers for path-breaking GEOINT research in areas of potential interest to NGA.

CMMT supports theoretical and computational materials research in the topical areas represented in DMR's Topical Materials Research Programs (these are also variously known as Individual Investigator Award (IIA) Programs, or Core Programs, or Disciplinary Programs), which include: Condensed Matter Physics (CMP), Biomaterials (BMAT), Ceramics (CER), Electronic and Photonic Materials (EPM), Metals and Metallic Nanostructures (MMN), Polymers (POL), and Solid State and Materials Chemistry (SSMC). The CMMT program supports fundamental research that advances conceptual understanding of hard and soft materials, and materials-related phenomena; the development of associated analytical, computational, and data-centric techniques; and predictive materials-specific theory, simulation, and modeling for materials research. First-principles electronic structure, quantum many-body and field theories, statistical mechanics, classical and quantum Monte Carlo, and molecular dynamics, are among the methods used in the broad spectrum of research supported in CMMT. Research may encompass the advance of new paradigms in materials research, including emerging data-centric approaches utilizing data-analytics or machine learning.

The Acquisition Research Program (ARP) (www.acquisitionresearch.net) conducts and supports research in academic disciplines that bear on public procurement policy and management. These include economics, finance, financial management, information systems, organization theory, operations management, human resources management, risk management, and marketing, as well as the traditional public procurement areas such as contracting, program/project management, logistics, test and evaluation and systems engineering management. The ARP is interested in innovative proposals that will provide unclassified and non-proprietary findings suitable for publication in open scholarly literature. Studies of government processes, systems, or policies should also expand the body of knowledge and theory of processes, systems, or policies outside the government. The following research areas are of special interest: Leading-edge techniques in data collection, management, visual analytics and decision-making; Robust risk modeling techniques; Performance metrics and methodologies; Collaboration and cross-functional teams; and, Model-Based Acquisition. Offerors bear prime responsibility for the design, management, direction and conduct of research. Researchers should exercise judgment and original thought toward attaining the goals within broad parameters of the research areas proposed and the resources provided. Offerors are encouraged to be creative in the selection of the technical and management processes and approaches and consider the greatest and broadest impact possible.

Through this Funding Opportunity Announcement (FOA), the National Cancer Institute (NCI) as a part of its Beau Biden Cancer Moonshot Initiative invites submission of applications requesting support for projects that will accelerate cancer research. Specifically, this FOA targets the following area designated as a scientific priority by the Blue Ribbon Panel (BRP) as Recommendation I: Generation of Human Tumor Atlases. The overarching goal of this FOA is to accelerate research efforts conducted and led by the Human Tumor Atlas Network (HTAN, humantumoratlas.org) via the implementation of three-dimensional (3D) imaging technologies that will allow for a comprehensive view of the dynamic multidimensional ecosystems that define tumors in humans. Each project will lead to the multiplexed 3D characterization of at least one cancer transition investigated by the HTAN (pre-malignant to malignant, primary to metastatic, therapy responsive to resistant). The data and analytical tools generated through this FOA will be made available for use by the research and clinical communities through the activities of the HTAN Data Coordinating Center.

Naval Surface Warfare Center (NSWC) Crane and the Office of the Undersecretary of Defense for Research and Engineering (OUSD(R&E))'s Joint Hypersonic Transition Office (JHTO) are interested in receiving research proposals in the following areas. Each will have a Period of Performance (PoP) of 12 months. a. Systems-level design of high-temperature composite materials and structures research utilization of fiber architectures and matrix compositions b. Novel position, navigation, and timing and adaptive flight controls c. Design-oriented models to optimize scramjet and multi-mode engines d. Simulation Methods for the Rapid Prediction of Hypersonic Environments e. Addressing the flow path processes that occur in rectangular or curved inlets and isolators including the destabilization that may occur due to junction flows or off-nominal flight conditions f. The development of methods and models including validation experiments and instrumentation to provide high quality data on multiphase blast properties and structural responses to structures g. Improving the understanding of rotating detonation rocket engine (RDRE) physics and developing design solutions for their inherent technical challenges h. Hypersonic Workforce Curricula Development

The Cyberinfrastructure for Sustained Scientific Innovation (CSSI) umbrella program seeks to enable funding opportunities that are flexible and responsive to the evolving and emerging needs in cyberinfrastructure (CI). This program continues the CSSI program by removing the distinction between software and data elements/framework implementations, and instead emphasizing integrated CI services, quantitative metrics with targets for delivery and usage of these services, and community creation. The CSSI umbrella program anticipates two classes of awards: Elements: These awards target small groups that will create and deploy robust services for which there is a demonstrated need, and that will advance one or more significant areas of science and engineering. Framework Implementations: These awards target larger, interdisciplinary teams organized around the development and application of services aimed at solving common research problems faced by NSF researchers in one or more areas of science and engineering, and resulting in a sustainable community framework providing CI services to a diverse community or communities. Prospective Principal Investigators (PIs) should be aware that this is a multi-directorate activity and that they are encouraged to submit proposals with broad, interdisciplinary interests. Further, not all divisions are participating at the same level and division-specific priorities differ. Prospective PIs should also refer to the directorate/division-specific descriptions contained in Section II of this solicitation.

The CDS&E-MSS program accepts proposals that engage with the mathematical and statistical challenges presented by (1) the ever-expanding role of computational experimentation, modeling, and simulation on the one hand, and (2) the explosion in production and analysis of digital data from experimental and observational sources on the other. The goal of the program is to promote the creation and development of the next generation of mathematical and statistical software tools, and the theory underpinning those tools, that will be essential for addressing these challenges. The research supported by the CDS&E-MSS program will aim to advance mathematics or statistics in a significant way and will address computational or big-data challenges. Proposals of interest to the program must include a Principal Investigator or co-Principal Investigator who is a researcher in an area supported by the Division of Mathematical Sciences. The program welcomes submission of proposals that include multidisciplinary collaborations or provide opportunities for training through research involvement of junior mathematicians or statisticians. This program is part of the wider NSF Computational and Data-enabled Science and Engineering (CDS&E) enterprise.

This Funding Opportunity Announcement (FOA) solicits resource grant applications for projects that will bring useful, usable health information to health disparity populations and their health care providers. Access to useful, usable, understandable health information is an important factor when making health decisions. Proposed projects should exploit the capabilities of computer and information technology and health sciences libraries to bring health-related information to consumers and their health care providers.

The Office of Naval Research (ONR), ONR Global, and Marine Corps Warfighting Lab (MCWL) are interested in receiving proposals for Long-Range S&T Projects which offer potential for advancement and improvement of Navy and Marine Corps operations. Readers should note that this is an announcement to declare ONR, ONRG and MCWLs broad role in competitive funding of meritorious research across a spectrum of science and engineering disciplines.

EarthCube is a community-driven activity sponsored through a partnership between the NSF Directorate for Geosciences (GEO) and the Office of Advanced Cyberinfrastructure (OAC) within the Directorate for Computer & Information Science & Engineering (CISE) to transform research in the academic geosciences community. EarthCube aims to create a well-connected and facile environment to share data and knowledge in an open, transparent, and inclusive manner, thus accelerating our ability to understand and predict the Earth system. Achieving EarthCube will require a long-term dialog between NSF and the interested scientific communities to develop cyberinfrastructure that is thoughtfully and systematically built to meet the current and future requirements of geoscientists. New avenues will be supported to gather community requirements and priorities for the elements of EarthCube, and to capture the best technologies to meet these current and future needs. The EarthCube portfolio will consist of interconnected projects and activities that engage the geosciences, cyberinfrastructure, computer science, and associated communities. The portfolio of activities and funding opportunities will evolve over time depending on the status of the EarthCube effort and the scientific and cultural needs of the geosciences community.

The MCA offers an opportunity for scientists and engineers at the Associate Professor rank (or equivalent) to substantively enhance and advance their research program through synergistic and mutually beneficial partnerships, typically at an institution other than their home institution. Projects that envision new insights on existing problems or identify new but related problems previously inaccessible without new methodology or expertise from other fields are encouraged. Partners from outside the PI's own sub-discipline or discipline are encouraged, but not required, to enhance interdisciplinary networking and convergence across science and engineering fields. By (re)-investing in mid-career investigators, NSF aims to enable and grow a more diverse scientific workforce (more women, persons with disabilities, and underrepresented minorities) at high academic ranks, who remain engaged and active in cutting-edge research.

The Law & Science Program considers proposals that address social scientific studies of law and law-like systems of rules, as well as studies of how science and technology are applied in legal contexts. The Program is inherently interdisciplinary and multi-methodological. Successful proposals describe research that advances scientific theory and understanding of the connections between human behavior and law, legal institutions, or legal processes; or the interactions of law and basic sciences, including biology, computer and information sciences, STEM education, engineering, geosciences, and math and physical sciences. Scientific studies of law often approach law as dynamic, interacting with multiple arenas, and with the participation of multiple actors. Fields of study include many disciplines, and often address problems including, though not limited, to: Crime, Violence, and Policing Cyberspace Economic Issues Environmental Science Evidentiary Issues Forensic Science Governance and Courts Human Rights and Comparative Law Information Technology Legal and Ethical Issues related to Science Legal Decision Making Legal Mobilization and Conceptions of Justice Litigation and the Legal Profession Punishment and Corrections Regulation and Facilitation of Biotechnology (e.g., Gene Editing, Gene Testing, Synthetic Biology) and Other Emerging Sciences and Technologies Use of Science in the Legal Processes

A key focus of the design of modern computing systems is performance and scalability, particularly in light of the limits of Moore's Law and Dennard scaling. To this end, systems are increasingly being implemented by composing heterogeneous computing components and continually changing memory systems as novel, performant hardware surfaces. Applications fueled by rapid strides in machine learning, data analysis, and extreme-scale simulation are becoming more domain-specific and highly distributed. In this scenario, traditional boundaries between hardware-oriented and software-oriented disciplines increasingly are blurred. Achieving scalability of systems and applications will therefore require coordinated progress in multiple disciplines such as computer architecture, high-performance computing (HPC), programming languages and compilers, security and privacy, systems, theory, and algorithms. Cross-cutting concerns such as performance (including, but not limited to, time, space, and communication resource usage and energy efficiency), correctness and accuracy (including, but not limited to, emerging techniques for program analysis, testing, debugging, probabilistic reasoning and inference, and verification), security and privacy, robustness and reliability, domain-specific design, and heterogeneity must be taken into account from the outset in all aspects of systems and application design and implementation.

Growing Convergence Research (GCR) at the National Science Foundation was identified as one of 10 Big Ideas. Convergence research is a means for solving vexing research problems, in particular, complex problems focusing on societal needs. It entails integrating knowledge, methods, and expertise from different disciplines and forming novel frameworks to catalyze scientific discovery and innovation. GCR identifies Convergence Research as having two primary characteristics: Research driven by a specific and compelling problem. Convergence Research is generally inspired by the need to address a specific challenge or opportunity, whether it arises from deep scientific questions or pressing societal needs. Deep integration across disciplines. As experts from different disciplines pursue common research challenges, their knowledge, theories, methods, data, research communities and languages become increasingly intermingled or integrated. New frameworks, paradigms or even disciplines can form sustained interactions across multiple communities. A distinct characteristic of convergence research, in contrast to other forms of multidisciplinary research, is that from the inception, the convergence paradigm intentionally brings together intellectually diverse researchers and stakeholders to frame the research questions, develop effective ways of communicating across disciplines and sectors, adopt common frameworks for their solution, and, when appropriate, develop a new scientific vocabulary. Research teams practicing convergence aim at developing sustainable relationships that may not only create solutions to the problem that engendered the collaboration, but also develop novel ways of framing related research questions and open new research vistas.

The objective of the Cybersecurity Innovation for Cyberinfrastructure (CICI) program is to develop, deploy and integrate solutions that benefit the broader scientific community by securing science data, workflows, and infrastructure. CICI recognizes the unique nature of modern, rapid collaborative science and the breadth of security expertise, infrastructure and requirements among different practitioners, researchers, and scientific projects. CICI seeks projects in three program areas: Usable and Collaborative Security for Science (UCSS): Projects in this program area should support novel and applied security and usability research that facilitates scientific collaboration, encourages the adoption of security into the scientific workflow, and helps create a holistic, integrated security environment that spans the entire scientific CI ecosystem. Reference Scientific Security Datasets (RSSD):Projects in this program area should capture the unique properties of scientific workflows and workloads as reference data artifacts to support reproducible security research and protect the scientific process. Scientific Infrastructure Vulnerability Discovery (SIVD): Projects in this program area should develop and apply techniques to proactively discover vulnerabilities and weaknesses in scientific infrastructure.