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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.

NineSigma, representing the Electric Power Research Institute (EPRI), invites proposals from organizations and companies for technologies and digital tools to provide real-time feedback from various sensory inputs for adaptive welding applications The ideal solution will collate and analyse data from the following inputs. Real-time imaging data from vision systems Real-time weld, groove and joint profile data from laser profiler Weld parameter data acquisition Acoustics and vibration (accelerometer) data analysis

The NSF's vision for Advanced Computing Infrastructure (ACI), which is part of its Cyberinfrastructure for 21st Century Science and Engineering (CIF21), focuses specifically on ensuring that the science and engineering community has ready access to the advanced computational and data-driven capabilities required to tackle the most complex problems and issues facing today's scientific and educational communities. To accomplish these goals requires advanced computational capabilities within the context of a multilevel comprehensive and innovative infrastructure that benefits all fields of science and engineering. Previous solicitations have concentrated on enabling petascale capability through the deployment and support of a world-class High Performance Computing (HPC) environment. In the past decade the NSF has provided the open science and engineering community with a number of state-of-the art HPC assets ranging from loosely coupled clusters, to large scale instruments with many thousands of computing cores communicating via fast interconnects, and more recently with diverse heterogeneous architectures. Recent developments in computational science have begun to focus on complex, dynamic and diverse workflows. Some of these involve applications that are extremely data intensive and may not be dominated by floating point operation speed. While a number of the earlier acquisitions have addressed a subset of these issues, the current solicitation emphasizes this even further.

The National Geographic Society is accepting applications for its Participatory Science program, which supports the development or innovative use of data-driven, technology-powered tools that increase the understanding, preservation, and protection of our planet. Applicants should propose tools that support citizen science work, particularly data collection or data analysis, in ways that create learning experience for citizen scientists, including students. Priority will be given to research, education, and technology projects that create and execute new digital applications, transform existing applications and products, or use current technologies to do one or more of the following: teach students and other citizen scientists about the planet using experiential, crowdsourced technology; encourage individuals who engage with these technologies and projects to build the attitudes, skills, and knowledge necessary to become stewards of the planet and contribute to solving real-world issues; and generate data and/or develop open-source technologies that contribute to scientific inquiry and advance our understanding of the planet.

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.

The NSF Mid-scale Research Infrastructure-2 Program (Mid-scale RI-2) supports implementation of projects that comprise any combination ofequipment, instrumentation, computational hardware and software, and the necessary commissioning and human capital in support of implementation of the same. The total cost for Mid-scale RI-2 projects ranges from $20 million to below the minimum award funded by the Major Research Equipment and Facilities Construction (MREFC) Program, currently $70 million. Mid-scale RI-2 projects will directly enable advances in any of the research domains supported by NSF, including STEM education. Projects may also include upgrades to existing research infrastructure. The Mid-scale RI-2 Program emphasizes strong scientific merit and response to an identified need of the research community, technical and managerial readiness for implementation, and a well-developed plan for student training and involvement of a diverse workforce in mid-scale facility development, and/or associated data management. Mid-scale RI-2 will consider only the implementation (typically construction or acquisition) stage of a project, including a limited degree of advanced development immediately preparatory to implementation. It is thus intended that Mid-scale RI-2 will support projects in high states of readiness for implementation, i.e., those that have already matured through previous developmental investments.

NSF invites proposals for the acquisition and deployment of a High Performance Computing (HPC) system, called the Phase 1 system, with the option of a possible future upgrade to a leadership-class computing facility. The Phase 1 system will serve two important and complementary purposes: It will serve as a robust, well-balanced, and forward-looking computational asset for a broad range of research topics for which advances in fundamental understanding require the most extreme computational and data analysis capabilities; and It will serve as an evaluation platform for testing and demonstrating the feasibility of an upgrade to a leadership-class facility five years following deployment.

NSF invites proposals for the acquisition and deployment of a High Performance Computing (HPC) system, called the Phase 1 system, with the option of a possible future upgrade to a leadership-class computing facility. The Phase 1 system will serve two important and complementary purposes: It will serve as a robust, well-balanced, and forward-looking computational asset for a broad range of research topics for which advances in fundamental understanding require the most extreme computational and data analysis capabilities; and It will serve as an evaluation platform for testing and demonstrating the feasibility of an upgrade to a leadership-class facility five years following deployment.

The first is intended to complement previous NSF investments in advanced computational infrastructure.  Consistent with the ACI Strategic Plan, the current solicitation is focused on expanding the use of high end resources to a much larger and more diverse community.   The second type is devoted to the increasing pressure on the existing infrastructure to store and process very large amounts of data coming from simulation and from experimental resources such as telescopes, genome data banks or sensors.