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The Engineering for Natural Hazards (ENH) program supports fundamental research that advances knowledge for understanding and mitigating the impact of natural hazards on constructed civil infrastructure.  Natural hazards considered by the ENH program include earthquakes, windstorms (such as tornadoes and hurricanes), tsunamis, storm surge, and landslides.  The constructed civil infrastructure supported by the ENH program includes building systems, such as the soil-foundation-structure-envelope-nonstructural system, as well as the façade and roofing, and other structures, geostructures, and underground facilities, such as tunnels.  While research may focus on a single natural hazard, research that considers civil infrastructure performance over its lifetime in the context of multiple hazards, that is, a multi-hazard approach, is encouraged.  Research may integrate geotechnical, structural, and architectural engineering advances with discoveries in other science and engineering fields, such as earth and atmospheric sciences, materials science, mechanics of materials, dynamic systems and control, systems engineering, decision theory, risk analysis, high performance computational modeling and simulation, and social, behavioral, and economic sciences.  Multi-disciplinary and international collaborations are encouraged.  The ENH program encourages research integrated with knowledge dissemination and activities that can lead to broader societal benefit for reducing the impact of natural hazards on civil infrastructure.

The Air Force Research Laboratory (AFRL) Space Vehicle Directorate (RV) is interested in receiving proposals from all offerors to advance state of the art technology and scientific knowledge supporting all aspects of space systems including payload adapters, on-orbit systems, communications links, ground systems, and user equipment. Efforts will include basic and advanced research, advanced component and technology development, prototyping, and system development and demonstration and will span the range from concept and laboratory experimentation to testing/demonstration in a relevant environment. Specific tasks include design, development, analysis, fabrication, integration, characterization, testing/experimentation, and demonstration of hardware and software products.

The Energy, Power, Control, and Networks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN's goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

The Energy, Power, Control, andNetworks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN’s goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

First Round of HPC4Mtls Solicitation is Now Open The first HPC4Mtls Program solicitation seeks concept papers that will address key challenges in developing, modifying, and/or qualifying new or modified materials that perform well in severe and complex energy application environments using high performance computing, modeling, simulation, and data analysis. For each of the program offices supporting this solicitation, we provide brief descriptions of their mission and the topics of interest to them. Deadline for concept paper submission is April 19, 2018 at 11:59 pm PDT.

The research opportunity described in this announcement falls under the following sections of the BAA: Appendix 1 "Program Description," * Section I entitled "Expeditionary Maneuver Warfare & Combating Terrorism (Code 30); specific thrusts and focused research area: * Paragraph E. "ONR 30 Decision Support, AI, Machine Learning and Graph Analysis Program," Technology Investment area 3, entitled "Modeling/ Machine Learning/ /Artificial Intelligence" *

This Funding Opportunity Announcement (FOA) invites applications that seek to apply one or more innovative methodologies in communication research across the cancer control continuum, from prevention, early detection, diagnosis, treatment, and survivorship, to end of life. Applications to this FOA should utilize one or more of the following analytic approaches, methods, and data sources, including but not limited to social media data mining, Natural Language Processing (NLP) techniques, online social network analysis, crowdsourcing research tools (e.g., mTurk), online search data, Ecological Momentary Assessment, neuroscience and biobehavioral approaches to communication, and geographic information systems. Studies should assess outcomes related to cancer prevention and control (e.g., knowledge, attitudes, beliefs, perceived risk, decision making in screening and treatment, information inequalities, social support, shared decision making, persuasion, caregiving, behavioral intentions, preventive behaviors, and policy support, among others). Also listed under R21

The technology demonstrations that result from this BAA will substantially improve the Air Force's capability to conduct missions in a variety of environments while minimizing the risks to Airmen. The overall impact of integration of autonomous systems into the mission space will enable the Air Force to operate inside of the enemy's decision loop. STAT will develop and apply autonomy technologies to enhance the full mission cycle, including mission planning, mission execution, and post-mission analysis. Particular areas of interest include multi-domain command and control, manned-unmanned teaming, and information analytics. The technology demonstrations that result from this BAA will substantially improve the Air Force's capability to conduct missions in a variety of environments while minimizing the risks to Airmen. The overall impact of integration of autonomous systems into the mission space will enable the Air Force to operate inside of the enemy's decision loop. This effort plans to demonstrate modular, transferable, open system architectures, and deliver autonomy technologies applicable to a spectrum of multi-domain applications.

This R18 Request for Application (RFA) calls for the creation and utilization of Patient Safety Learning Laboratories. These learning laboratories are places and networks where transdisciplinary teams identify closely related threats to diagnostic or treatment efforts associated with a high burden of harm and cost. Following a systems engineering methodology, the learning laboratories stretch professional boundaries, envision innovative designs, and take advantage of brainstorming and rapid prototyping techniques that other leading industries employ. Promising prototypes undergo further develop-test-revise iterations, and subsequent integration as a working system. After further improvements are made to the integrated working system, its efficacy is evaluated in a realistic simulated or clinical setting. While applicants will select the area of diagnostic or treatment focus they consider of high significance, a flexible methodology -- problem analysis, design, development, implementation, and evaluation -- is required that parallels a systems engineering process to give an underlying structure to the work undertaken.

This Funding Opportunity Announcement (FOA) seeks grant applications to develop major advances in genomic technologies. Advances in genomics and more broadly in biomedical research have been greatly facilitated by significant and sustained genomics technology throughput increases, cost decreases, and improvements in ease of use. The proposed technology development work should allow comprehensive genomic analysis of features not assayable today, or an increase of no less than an order of magnitude improvement in an existing technology in terms of data quality, throughput, efficiency or comprehensiveness (individually or in combination). This FOA explicitly excludes the development of novel technologies for DNA sequencing and for direct RNA sequencing; those projects should respond to a parallel set of FOAs (RFA-HG-18-001, RFA-HG-18-002, and RFA-HG-18-003).

wards will be made as grants, cooperative agreements, contracts, and inter- or intra-agency transfers, depending on the nature of the work proposed, the proposing organization, and/or program requirements. The typical period of performance for an award is three years, but some programs may allow up to five years and others specify shorter periods. Organizations of every type, domestic and foreign, Government and private, for profit and not-for-profit, may submit proposals without restriction on teaming arrangements. Note that it is NASA policy that all research involving non-U.S. organizations will be conducted on the basis of no exchange of funds. Awards range from under $100K per year for focused, limited efforts (e.g., data analysis) to more than $1M per year for extensive activities (e.g., development of hardware for science experiments and/or flight). The funds available for awards in each program element offered in ROSES-2018 range from less than one to several million dollars, which allows for selection from a few to as many as several dozen proposals, depending upon the program objectives and the submission of proposals of merit. Electronic submission of proposals is required by the respective due dates for each program element and must be submitted by an authorized official of the proposing organization.

The Mind, Machine and Motor Nexus (M3X) program supports fundamental research at the intersection of mind, machine and motor. A distinguishing characteristic of the program is an integrated treatment of human intent, perception, and behavior in interaction with embodied and intelligent engineered systems and as mediated by motor manipulation. M3X projects should advance the holistic analysis of cognition and of embodiment as present in both human and machine elements. This work will encompass not only how mind interacts with motor function in the manipulation of machines, but also how, in turn, machine response and function may shape and influence both mind and motor function.

The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers. The first group consists of researchers in the area of formal methods, which, for the purposes of this solicitation, is broadly defined as principled approaches based on mathematics and logic, including modeling, specification, design, program analysis, verification, synthesis, and programming language-based approaches. The second group consists of researchers in the "field," which, for the purposes of this solicitation, is defined as a subset of areas within computer and information science and engineering that currently do not benefit from having established communities already developing and applying formal methods in their research. This solicitation limits the field to the following areas that stand to directly benefit from a grounding in formal methods: computer networks, cyber-human systems, distributed /operating systems, embedded systems, and machine learning. Other field(s) may emerge as priority areas for the program in future years, subject to the availability of funds.

Scientific machine learning is a core component of artificial intelligence and a computational technology that can be trained, with scientific data, to augment or automate human skills. Major research advances will be enabled by harnessing DOE investments in massive amounts of scientific data, software for predictive models and algorithms, high-performance computing (HPC) and networking platforms, and the national workforce. The crosscutting nature of machine learning and AI provides strong motivation for formulating a prioritized research agenda. Scientific Machine Learning and Artificial Intelligence (Scientific AI/ML) will have broad use and transformative effects across the research communities supported by DOE. Accordingly, a 2019 Basic Research Needs workshop report identified six Priority Research Directions. The first three PRDs describe foundational research themes that are common to the development of Scientific AI/ML methods and correspond to the need for domain-awareness, interpretability, and robustness. The other three PRDs describe capability research themes and correspond to the three major use cases of massive scientific data analysis (PRD #4), machine learning-enhanced

It is NASA's intent to update these foci and compete this element on an annual basis to best address scientific and programmatic priorities: 1. High-End Computing for ESI: Research advancing the use of High-End Computing (HEC) resources to answer specific questions in solid-Earth science. This subsection welcomes proposals addressing observational network design and augmentation, automated processing of large datasets, and advanced analysis and simulation. Proposals that demonstrate a clear need and robust plan for use of NASA HEC resources are especially encouraged. 2. Geomagnetic Research: Research that utilizes remotely sensed geomagnetic observations to further advance our understanding of the solid Earth. 3. Strengthening ESI Community Knowledge and Skills: New ESI-relevant activities that strengthen knowledge and skills of graduate students and/or postdoctoral researchers and broaden community awareness of the ESI mission. Prospective proposers are encouraged to contact the program point of contact to discuss the relevance of their proposal.

DARPA is soliciting innovative research proposals in the area of advanced design and analysis tools that can establish cyber resiliency as an explicit system property. Proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, or systems.

The High-Performance Computing for Manufacturing (HPC4Mfg) Program seeks qualified industry partners to participate in short-term, collaborative projects with the Department of Energy's (DOE's) national laboratories. Through support from the Advanced Manufacturing Office of the DOE Office of Energy Efficiency and Renewable Energy (EERE), selected industry partners will be granted access to High Performance Computing (HPC) facilities and experienced staff at DOE National Laboratories. The collaborations will address key challenges in U.S. manufacturing by apply modeling, simulation, and data analysis to the manufacturing of materials with the intent to improve energy efficiency, increase productivity, reduce cycle time, enable next-generation technologies, test control system algorithms, investigate intensified processes, lower energy cost, and accelerate innovation. Projects must demonstrate potential impact to energy efficiency in manufacturing and/or the development of new clean energy technologies with a potential for broad national impact. We solicit proposals in the following primary areas:

This Funding Opportunity Announcement (FOA) encourages applications that will develop novel technologies and/or tools for the isolation and characterization of extracellular vesicles (EVs) of Central Nervous System (CNS) origin. The primary focus of the technology development includes robust and reproducible CNS-EV isolation methods. Specifically, there is a need to establish technologies for the isolation and purification of CNS-EVs from peripheral samples and the characterization of CNS-EV types, cargos, and origin, as well as to validate these methods for further analyses. Validation of these technologies may include the analysis of the full range of EV composition such as RNA, proteins, lipids, and metabolites.

This Funding Opportunity Announcement (FOA) encourages innovative research to enhance the quality of measurements of dietary intake and physical activity. Applications submitted under this FOA are encouraged to include development of: novel assessment approaches; better methods to evaluate instruments; assessment tools for culturally diverse populations or various age groups, including children and older adults; improved technology or applications of existing technology; statistical methods/modeling to improve assessment and/or to correct for measurement errors or biases; methods to investigate the multidimensionality of diet and physical activity behavior through pattern analysis; or integrated measurement of diet and physical activity along with the environmental context of such behaviors.

We are seeking proposals for new research that will support and enhance the activities of the Consortium for the Valuation of Applications Benefits Linked to Earth Science (VALUABLES), a new consortium at RFF made possible through a partnership with the National Aeronautics and Space Administration (NASA). VALUABLES is focused on advancing innovative uses of existing methods and developing new techniques for valuing the information provided by Earth observations, especially those derived from satellites and aircraft. Any area in which Earth observations play a role may be addressed, including applications relating to human health, air quality, water resources, ecosystem services, natural disasters, food security and agriculture, wildland fires, energy, urban development, and transportation and infrastructure. However, the use of remotely sensed data must be a key component of the analysis. In addition, we especially welcome proposals that focus on evaluating the socioeconomic impacts of applications of Earth observations for solving pressing societal problems and that quantify, in monetary terms, the value of Earth observations in specific applications. In so doing, proposals should clearly describe how information from Earth observations makes improvements to decision making and the value of those improvements. Applicants may propose to quantify the private and/or social benefits of applications of Earth observations, including nonmarket benefits. The Macauley Award is open to researchers at US-based universities and nonprofit research institutions. Interdisciplinary research teams are preferred, and teams that involve both economists and Earth scientists are particularly encouraged.