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3DEP was developed to respond to needs for high-quality topographic data and for a wide range of other three-dimensional representations of the Nation's natural and constructed features. This Broad Agency Announcement (BAA) is issued to facilitate the collection of lidar and derived elevation data for the 3D Elevation Program (3DEP). The BAA continues the USGSâ¿¿s long-standing approach to elevation data acquisition through a combination of contracting through the USGS Geospatial Products and Services Contracts (GPSC) and partner acquisitions. The BAA is meant to provide increased visibility to these existing processes for data acquisition partnerships to the broadest stakeholder community possible.

The purpose of this Funding Opportunity Announcement (FOA) is to provide regional access for cryoelectron microscopy (cryoEM) laboratories to state-of-the-art data collection capabilities. NIGMS will support consortia of established and early stage investigator laboratories whose research has an established specialization in and dependence on cryoEM. These laboratories will coordinate with each other to share facilities and resources for direct electron detection. Consortia will consist of a host institution which already has a modern high-performing cryoEM installation and proven capabilities for high-resolution data collection, partnered with regional participating institutions. A consortium will support surplus capacity for cryoEM data collection (infrastructure and services) at the host institution and make it available as a resource for the participating regional institutions. Projects will support access for cryoEM laboratories at participating institutions to resources and services at host sites. Projects will (a) contribute to the fixed costs of maintaining the host facility and extend services in proportion to the resources dedicated to the regional users and (b) support access to the facility by the regional laboratories. The host institution need not already have an electron detector; this FOA can help fund acquisition of direct detection equipment. Support is limited to enabling the participating cryoEM laboratories to collect data and perform the initial stages of processing raw images, and does not include other research activities. Consortia will consist of a minimum of 3-5 institutions; award budgets will depend on the number and data collection needs of the regional participating cryoEM laboratories. This initiative is not intended to support service centers of the traditional type in which the host laboratory performs the cryoEM analysis for non-specialist collaborators.

This agreement provides for the transfer of funds from the National Park Service to Colorado Natural Heritage Program of Colorado State University for support in developing and applying sound science to identify, inform, implement, and evaluate the application of climate change adaptation strategies across the U.S. national park service system. Supporting and tracking adaptation requires knowledge and expertise in scientific information gathering and synthesis, database and data management, and climate data acquisition, management, analysis, visualization, and presentation. The scope of work required to achieve the objectives includes database management and data analysis, visualization, and presentation, and additional and supporting work will include literature searches, reviews, and syntheses, as well as help preparing presentations and other science-based products.

NSF solicits proposals to manage the operations and maintenance of the National Ecological Observatory Network (NEON), an NSF-funded major facility project. NEON comprises terrestrial, aquatic, atmospheric, and remote sensing measurement infrastructure and cyberinfrastructure that deliver standardized, calibrated data to the scientific community through a single, openly accessible data portal. NEON infrastructure is geographically distributed across the United States, including Alaska, Hawaii and Puerto Rico, and will generate data for ecological research over a 30-year period. NEON is designed to enable the research community to ask and address their own questions on a regional to continental scale around the environmental challenges identified as relevant to understanding the effects of climate change, land-use change and invasive species patterns on the biosphere. The NSF NEON program, which is part of the Centers and Cooperative Agreements Cluster in the Division of Biological Infrastructure, manages the NEON award in collaboration with the NSF Large Facilities Office and the NSF Division of Acquisition and Cooperative Support.

The Hazard Mitigation and Structural Engineering (HMSE) program supports fundamental research to mitigate impacts of natural and anthropogenic hazards on civil infrastructure and to advance the reliability, resiliency, and sustainability of buildings and other structures. Hazards considered within the program include earthquake, tsunami, hurricane, tornado and other loads, as well as explosive and impact loading. Resiliency of buildings and other structures include structural and non-structural systems that, in totality, permit continued occupation or operation in case of an impact by a hazard. Research is encouraged that integrates structural and architectural engineering advances with discoveries in other science and engineering fields, such as earth and atmospheric sciences, material science, mechanics of materials, sensor technology, high performance computational modeling and simulation, dynamic system and control, and economics. The program seeks to fund transformative and cost-effective innovations for hazard mitigation of both new and rehabilitated buildings and other structures. Research in structural and architectural engineering is encouraged that extends beyond mature or current construction materials into investigations of smart and sustainable materials and technologies, and considers the structures in their entirety. In addition, the program funds research on structural health monitoring that goes beyond data acquisition to include the holistic system, integrating condition assessment and decision making tools to improve structural performance