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This map depicts lands owned andor administered by the U.S. Fish and Wildlife Service at San Juan Islands National Wildlife Refuge.

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<p>This project created a pilot version of the software tool work control system to run on a tablet by modifying the existing template and beginning an initial investigation into the processes needed to make the mobile software tool work well with the existing database. A tablet and the mobile software was used in conjunction with software currently owned by Stennis. From an Information Technology (IT) security standpoint, proper implementation strategies (e.g. Secured Wi-Fi, 3G cellular networks, and docking stations) were considered for field use of the system. A representative from IT security helped facilitate discussions for proper implementation strategies with support from developers to assess feasibilities of such strategies.</p><p>Primary project objectives included the following:</p><ul><li>Create a pilot version of the work control system to run on an tablet by modifying an existing template</li><li>Begin an initial investigation into the processes needed to make the control system work well with the existing database.</li></ul><p>From an IT security standpoint, consider proper implementation strategies (e.g. Secured Wi-Fi, 3G cellular networks, and docking stations) for field use of such a system.</p>

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This proposal details a novel mobile data transceiver solution that supports standalone wireless sensors and concurrently acts as a gateway between multiple sensor webs. This innovation uses Software Defined Radio (SDR) technology to communicate with a variety of sensor technologies using many different radio waveforms and communication protocols. The proposed system is designed to be adaptable to mission requirements and all aspects of its operation can be remotely modified after deployment. When possible, the solution uses commercial of the shelf technology (COTS) components and incorporates open data operability standards for information visualization.

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ASTER Global Digital Elevation Model GDEM DEM

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The Population Exposure Estimates in Proximity to Nuclear Power Plants, Locations data set combines information from a global data set developed by Declan Butler of Nature News and the Power Reactor Information System (PRIS), an up-to-date database of nuclear reactors maintained by the International Atomic Energy Agency (IAEA). The locations of nuclear reactors around the world are represented as point features associated with reactor specification and performance history attributes as of March 2012.

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National Veterans Small Business Engagement website - Atlanta webpage

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NODC Accession 0115221 includes meteorological, biological, physical and trawl data collected aboard the PANDALUS during cruises PA0101, PA0102, PA0103, PA0104, PA0201, PA0202, PA0203, PA0301, PA0302, PA0303, PA0401, PA0402, PA0403 and PA9901 in the Gulf of Alaska from 1999-08-27 to 2004-09-17. These data include SEA STATE, SPECIES IDENTIFICATION, SPECIES IDENTIFICATION - LIFE STAGE, species abundance and WIND SPEED. The instruments used to collect these data include trawl. These data were collected by Jack Piccolo, Jennifer L Boldt and Lewis J Haldorson of University of Alaska Fairbanks as part of NEP. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) submitted these data to NODC on 2013-10-31. The following is the text of the abstract provided by BCO-DMO: Coastal Gulf of Alaska Trawl Data Notes 1) This file was created to separate surface trawl samples used exclusively from 2001-2004 from gillnet and midwater trawl samples used in prior years. CPUE calculations based on these different gear types may not be directly comparable. 2) Gillnet and midwater trawl catch data from prior years will be reported separately. 3) Gear abbreviations: T = Surface Trawl 4) Gear description: Nordic 264 surface rope trawl (198-m long, 25-m wide, 35-m vertical height, equipped with a 1.2-cm mesh liner in cod end) towed at the surface. 5) Start times for trawls are when all warp wire and doors have been let out, and end times are when warp wire retrival begins. 6) Numbers of fish caught from an event listed in this file may not match the count of number of fish measured in the "Glength_September_2005" file because in some cases the number of fish measured was a subsample of total catch. 7) For cruises G01-3 and G02-2 field identifications of juvenile salmon were inconsistent. Pink, chum, and sockeye, therefore, are all grouped under salmon, unidentified juvenile, as noted in the comment column. Data Collector/Primary Contact (for more information): Lewis J. Haldorson Fisheries Division University of Alaska, Fairbanks 11120 Glacier Highway Juneau, AK 99801 lew.haldorson@uaf.edu (mailto:lew.haldorson@uaf.edu) Phone: 907-465-6446 FAX: 907-465-6447 Secondary Contact: Jack Piccolo UAF / SFOS 11120 Glacier Highway Juneau, AK 99801 ftjjp1@uaf.edu (mailto:ftjjp1@uaf.edu) Phone: 907-796-2055

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Press kit for ISS mission Expedition 28 from 04/2011-11/2011. Press kits contain information about each mission overview, crew, mission timeline, benefits, and media contact information.

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China County-Level Data on Population (Census) and Agriculture, Keyed To 1:1M GIS Map consists of census, agricultural economic, and boundary data for the administrative regions of China for 1990. The census data includes urban and rural residency, age and sex distribution, educational attainment, illiteracy, marital status, childbirth, mortality, immigration (since 1985), industrial/economic activity, occupation, and ethnicity. The agricultural economic data encompasses rural population, labor force, forestry, livestock and fishery, commodities, equipment, utilities, irrigation, and output value. The boundary data are at a scale of one to one million (1:1M) at the county level. This dataset is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project, University of California-Davis China in Time and Space (CITAS) project, and the Columbia University Center for International Earth Science Information Network (CIESIN).

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This SBIR Phase I project will demonstrate monolayer and dual layer coating of SiC fiber by leveraging Laser Chemical Vapor Deposition techniques developed by Free Form Fibers for direct fiber production. Ceramic fibers, particularly SiC, must be coated in order to protect the fibers from oxidizing environments, and to allow their use in SiC CMC's. FFF's LCVD techniques can be modified for fast, high purity coating. The Phase I effort includes creating a custom reactor that leverages FFF's existing gas precursor delivery infrastructure, and passing existing monofilament SiC fiber through the reactor to coat with BN in real time. Reversing direction and coating the coated fiber with SiC will be done for dual layer coating. Phase II would scale the process to serially dualcoat a unidirectional moving parallel array of hundreds or thousands of moving fibers. If successful, industry would finally have a reliable in-line approach to fiber coating prior to tow production, because spreading and coating already-sized tows is nearly impossible. Based on prior coating experience and other related proposals, Phase I work would take us from TRL3 to TRL4. Phase II could take us to TRL4 or TRL5, either on a FFF or other commercial fiber production facility.

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A map service on the www depicting the recreation opportunity information that the Forest Service collects through the Recreation Portal and shares with the public on http://www.recreation.gov, the Forest Service World Wide Web pages (http://www.fs.fed.us/) and the Interactive Visitor Map. This recreation data contains detailed descriptions of recreational sites, areas, activities & facilities. Please note that the RECAREAID is the unique identifier present in point feature class and in the related tables as well. The RECAREAID is used as foreign key to access relate records. This published data is updated nightly from an XML feed maintained by the CIO Rec Portal team. This data is intended for public use and distribution.

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ABSTRACT: The Global Precipitation Climatology Project (GPCP) Version 2 data set includes global, monthly precipitation rates and associated random errors (RMSE), and a monthly precipitation climatology derived as an average from all GPCP data sets from January 1979 to December 1999. The data are derived from measured gauge data and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set: the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data sets and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set: the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.

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Romania, an eastern European country, is severely affected by a variety of natural hazards. These include frequent earthquakes, floods, landslides, soil erosion, and drought all of which have major social and economic impacts. Thus, there is a long tradition of study of these hazards by scientific researchers in Romania. This set of slides includes examples of landslides, rockfalls,sheet erosion, and mudflows. Romania has an area of 237,500 km2 and a great variety of geologic regions. Two-thirds of the country consists of hills, tablelands, and mountains of the Carpathian arch. The climate is dominantly temperate-continental and vegetation and soils vary widely with altitude. Altitude ranges from sea level to 2,544 meters above sea level at the highest point of the Romanian Carpathians. Romania's population in 1992 was 22.76 million inhabitants, or an average density of 95.8 people per square kilometer. The Vrancea Seismic Region of the southeastern part of the Carpathian Mountains is the most active subcrustal earthquake province of Europe. The region is characterized by high seismicity, with about three major earthquakes greater than magnitude (M) 7.0 occurring every century. The best studied earthquake of recent times occurred March 4, 1977, and had a magnitude of 7.2. This earthquake caused the death of 1,570 people, and destroyed 33,000 buildings. In addition to earthquakes, torrential rains are responsible for catastrophic floods, massive landslides, and major soil erosion. Mass movements are a significant hazard in the hilly and mountainous regions, particularly those underlain by flysch deposits. These deposits are complexes of folded and faulted sedimentary rocks containing marls, clays, shales, sandstones, and conglomerates. The distribution of mass movements in these deposits is controlled by various climatic, tectonic, and lithologic factors influenced by different land-management practices. There are significant regional differences among types of mass movements, the quantities of materials delivered from the slopes into adjacent stream channels, and risks to various human activities. In the Subcarpathians, formed predominantly of folded and faulted molasse deposits, slopes may be highly unstable. The instability is most frequently manifested by shallow (sheet) slides, landslides of medium depth, and mudflows typically 300-700 meters in length. The areas most affected by these features lie within the Curvature Subcarpathians in the Vrancea Seismic Region. In the Eastern Carpathians, formed predominantly of Cretaceous and Paleocene flysch deposits, periglacial or immediate postglacial colluvial materials are major sources of mass movements. These deposits generally range from 10 to 30 meters in depth, and landslides within them arecommonly activated or reactivated by regional deepening of the valley network in the long term, or deforestation practices by people. Because oftheir association with stream valleys, these landslides often affect towns, communication lines, and roads, and may partially or totally block valleys when they move. In the Moldlavian Plateau, the areas most affected by landslides occur on slopes built up of alternations of marls and clays, with intercalations of conglomerates and sandstones. In the Transylvanian Plateau deep landslides called "glimee" are commonly triggered by heavy rains. In the alpine belt of the Carpathian mountains, the most common mass movements are rockfalls and rock avalanches. These processes are mostcommon in the crystalline rocks on the steep slopes of glacial cirques and valleys. Sheet and gully erosion affect most of the hilly and mountainous regions of Romania. Agricultural lands on slopes steeper than 5% represent 42% ofthese regions and contribute to the bulk of sheet and gully erosion. About 20% of the agricultural lands are affected by high to very high erosionrates of 8-16 T/HA/year; 19% are subject to more moderate rates of 2-8 T/HA/Year; and about 3% are classified as slightly eroded. Highest erosion risks occur in the Curvature Subcarpathians, the Getic Subcarpathians, the north of the Getic Plateau, the central part of the Moldavian Plateau, and the west of the Translvanian Plateau. In these regions, large areas are affected by gully erosion which contributes to making about 5,000 ha/year unfit for the cultivation of crops. There is a corresponding loss of 30 million tons of soil per year. Factors related to gully erosion include poorly consolidated rocks, intense rainfall, and poor land-use practices. Mud volcanoes occur along active fault lines in the Curvature Subcarpathians, and are related to groundwater circulation under pressure.Mud volcanoes commonly are activated and reactivated during strong earthquakes. The largest mud volcanoes are located in the Berca Anticline Depression, a region rich in oil deposits. Upward movement of ground waterand oil there formed large, circular mud volcano plateaus 60-70 meters high with diameters of 200-300 meters. Within these plateaus, there are active and extinct mud volcano cones about one to three meters high. Because of the unusual formations, the region is protected from development and is a preserve for some of Romania's spectacular natural features.

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Interim NRPC report Indiana bat for Rafinesques bigeared bat Southeastern myotis, Northern longeared bat to determine status, habitat use preference. Arkansas State University is conducting research at Cache River NWR Arkansas.

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Monthly Medicare Advantage Enrollment by State, County, and Contract

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EDFacts ESEA Flexibility 2011-12 (EDFacts ESEA FLEX:2011-12) is one of 17 'topics' identified in the EDFacts documentation (in this database, each 'topic' is entered as a separate study); program data is available since 2005 at . EDFacts ESEA FLEX:2011-12 (ed.gov/about/inits/ed/edfacts) annually collects cross-sectional data from states about Title I, Part A funds allocation and state interventions in priority or focus schools at the school level. EDFacts ESEA FLEX:2011-12 data were collected using the EDFacts Submission System (ESS), a centralized portal and their submission by states is mandatory and required for benefits. Not submitting the required reports by a state constitutes a failure to comply with law and may have consequences for federal funding to the state. Key statistics produced from EDFacts ESEA FLEX:2011-12 are from 2 data groups with information on Title I Allocations to Priority/Focus Schools-Flex and State Interventions in to Priority/Focus Schools-Flex. For the purposes of this system, data groups are referred to as 'variables', as a result of the structure and format of EDFacts' data.

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This topographic elevation point data derived from multiple return light detection and ranging (LiDAR) represents 354.272 square miles of coastline for Rhode Island and Massachusetts. The LiDAR point cloud is delivered in LAS 1.2 format with the following classifications: Class 1: Unclassified Class 2: Ground Class 9: Water Class 10: Ignored Points Class 12: Overlap

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For the purposes of advancing integral field spectrograph (IFS) microlens capabilities, a new class of high-quality optics-grade nanostructured organic-inorganic nanocomposite three-dimensional (3D) gradient index (GRIN) microlens optical materials is proposed. In the Phase I program, solid state freeform (SFF) fabrication of high contrast 3D-gradient-index microlens array elements will be demonstrated using a research grade printer. A design of experiment will be conducted to optimize a series of 3D-GRIN films with axial, radial, and vertical gradient optical index patterns with microlenses of varying diameter, pitch, and focal length, including those symmetric and asymmetric. The films will be thoroughly characterized using optical coherent tomography and spectral interferometric techniques, and their power will be tested using collimated and converging light. A series of planar microlens arrays of varying shape, diameter, density, focal length will then be fabricated, and then planar films with two-surface microlens array, including masking, will be fabricated using the measured process parameters (i.e. Δn, Δn/(Δx,y,z), dispersion, etc.)

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These ESRI shape files are of National Park Service tract and boundary data that was created by the Land Resources Division. Tracts are numbered and created by the regional cartographic staff at the Land Resources Program Centers and are associated to the Land Status Maps. This data should be used to display properties that NPS owns and properties that NPS may have some type of interest such as scenic easements or right of ways.

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This dataset contains temperature and humidity profiles from the NOAA Microwave Integrated Retrieval System (MIRS) using sensor data from the Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. ATMS is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. MIRS was developed by the NOAA/NESDIS Center for Satellite Application and Research (STAR) and is produced operationally at the NOAA/NESDIS Office of Satellite and Product Operations (OSPO). The sounding (SND) products file contains temperature and water vapor profiles at 850, 900 and 950 millibars. Quality control metrics and flags defining retrieval product quality are also provided. Each product file encompasses one 32-second granule of data, corresponding to 4 scan lines of ATMS data. The products are distributed in netCDF-4 file format with metadata attributes included.

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Through its Electronic Document Information System (EDIS), the USITC provides an interface to extract investigation and document metadata through a Representational State Transfer (RESTful) architecture XML web service to provide key metadata to the user or application calling it. Investigation Data and Document Data may be extracted using this interface. The user of this interface may extract investigation data, including all investigations or investigation number or investigation and phase. The data may also be filtered by investigation status or investigation type. Investigation information displayed includes the following data elements: 1) Investigation Number, such as 337-406, without the Tariff Act ( -TA-) nomenclature. 2) Investigation Phase, such as Violation, Preliminary, Final 3) Investigation Type, such as Import Injury, Sec 337, Industry and Economic Analysis, Byrd Amendment and Rule Making. 4) Investigation Status, such as PreInstitution, Active, Inactive, Cancelled. 5) Investigation Title 6) A link to the documents within that investigation All documents stored in EDIS have metadata describing the content of each document. The user of this interface may extract document data by all or by document id. The data may also be filtered by investigation number, investigation phase, and document type. Document information displayed includes the following data elements: 1) Document ID - unique ID number for the document in EDIS 2) Document Type - identifies the type of document, such as 'Action Request' or 'Correspondence - USITC' 3) Security Level - identifies the security level of the document. This interface will only extract metadata available to external users: Public, Limited and Confidential. 4) Investigation Number, such as 337-406 5) Investigation Phase, such as Violation, Preliminary, Final 6) Investigation Status, such as PreInstitution, Active, Inactive, Cancelled. 7) Investigation Title 8) Investigation Type, such as Import Injury, Sec 337, Industry and Economic Analysis, Byrd Amendment and Rule Making. 9) Firm / Organization - name of the Firm filing the document. 10) Filed By - attorney filing the document. 11) On Behalf of - Company being represented on the filing; or the Office for internal USITC filings. 12) Document Date - date the document was authored or signed. 13) Official Received Date - date the document was provided to the USITC Dockets Office. Only Validated EDIS documents are included in this interface. Only Public, Limited and Confidential metadata are included. No document text or PDFs are included.

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The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). In addition to the preceding, required text, the Abstract should also describe the projection and coordinate system as well as a general statement about horizontal accuracy.

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CDBG activity related to acquisition, including disposition, clearance and demolition, and clean-up of contaminated Sites/brownfields.

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This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer. The DEMs created for this project were developed using the NOAA National Weather Service's Weather Forecast Office (WFO) boundaries. Because the WFO boundaries can cover large areas, the WFO DEM was divided into smaller DEMs to ensure more manageable file sizes. The Seattle (WA) WFO DEM was split into three smaller DEMs. They are divided along county lines and are: 1. Seattle (WA) WFO - Grays Harbor County 2. Seattle (WA) WFO - Clallam, Jefferson, Kitsap, Mason, Pierce, and Thurston Counties 3. Seattle (WA) WFO - Whatcom, San Juan, Skagit, Island, Snohomish, and King Counties This metadata record describes the DEM for Seattle (WA) WFO - Whatcom, San Juan, Skagit, Island, Snohomish, and King Counties. The DEM includes the best available lidar data known to exist at the time of DEM creation for the coastal areas of Whatcom, San Juan, Skagit, Island, Snohomish, and King Counties, that met project specifications. The DEM is derived from multiple LiDAR datasets collected between 2000 and 2009 for the Puget Sound LiDAR Consortium. Hydrographic breaklines used in the creation of the DEM were delineated using LiDAR intensity imagery generated from each constituent dataset. The DEMs are hydro flattened such that water elevations are less than or equal to 0 meters. The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 5 meters.

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This is an Arc/Info coverage consisting of 7 points representing known coordinates on the earth's surface at Pipe Spring National Monument, Arizona. One geodetic marker was placed by the National Park Service; four markers are survey markers of the four corners of the boundary (they reflect mapping accuracy and not survey accuracy). Other markers need to be located and added to this coverage. The geodetic markers were collected by a Trimble GeoXT GPS unit with external antenna, Hurricane, and post processed in GPS Pathfinder Office 3.0 for differential corrections. The seventh point representing a geodetic marker was collected using a Trimble GeoXT GPS unit with no external antenna and post processed in GPS Pathfinder Office 3.1 for differential corrections.