Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

Comprehensive dataset containing 16 verified Sara locations in United States with complete contact information, ratings, reviews, and location data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Plant Macrofossil. The data include parameters of plant macrofossil (population abundance) with a geographic _location of Louisiana, United States Of America. The time period coverage is from 6848 to 6838 in calendar years before present (BP). See metadata information for parameter and study _location details. Please cite this study when using the data.

Comprehensive dataset containing 40 verified Sara locations in Mexico with complete contact information, ratings, reviews, and location data.

The Species at Risk (SAR) Program is responsible for carrying out DFO’s mandate under the Species at Risk Act (SARA) to protect, recover and conserve all listed aquatic SAR in Canada. As part of this mandate, this spatial database has been developed to identify areas in which aquatic species listed under SARA may be found. Distribution and range information are identified for species listed as Endangered, Threatened or Special Concern under SARA. Distribution (range) polygons and lines were assembled by regional SARA biologists using the best available information, including COSEWIC status reports, recovery potential assessments, academic literature, and expert opinion. These spatial data support the protection, recovery and conservation of species listed as Endangered, Threatened or Special Concern under SARA. Species distributions are also described and displayed in Recovery Strategies, Action Plans and/or Management Plans. Discrepancies may exist between the distribution data shown in a species’ SARA recovery document and the current spatial data. Please contact DFO for more information on any data discrepancies.

This dataset contains the predicted prices of the asset SARA over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Contents 1 Data set description 1.1 Data set overview 1.2 Parameters 1.3 Processing 1.4 Data 1.5 Ancillary data 1.6 Software 1.7 Media/Format 2 Confidence level note 2.1 Confidence level overview 2.2 Review 2.3 Data quality 1. Data set description 1.1. Data set overview The output data of CENA sensor is basically neutral particle counts.CENA sensor operates in 3 instrument modes (coincidence Mode, counter M ode and Engineering Mode) and the content of the data coming from the CENA sensor is dependent on the instrument mode and the format of the data depends on the telemetry mode. The telemetry modes are Mass Accumulation Mode, TOF Accumulation Mode and Count Accumulation Mode.In Mass accumulation mode, TOF accumulation mode and Count accumulation mode, data coming from the sensor is being sorted by lookup tables and is being summed up into two types of accumulation matrixes (the accumulation matrix and the accumulation scaling matrix) during a time period. The accumulation matrix size changes depending on the binning parameters (energy, channel, phase and mass bins).For details on the CENA sensor of the SARA experiment and the data products, see the EAICD in the DOCUMENT directory. 1.2. Parameters The measured parameter is basically raw neutral particle counts. 1.3. Processing No processing beyond unpacking has been applied to the telemetry data. 1.4. Data Each data product contains all data from one orbit. The data product contain housekeeping data as well as science data as scaling matrix(total counts) and accumulation matrix except for the counter mode operation of CENA where there will be no scaling matrix.The instrument mode and telemetry mode is reflected in the file name (refer to the EAICD in the DOCUMENT directory).CENA data is archived using the storage format of PDS ARRAY of COLLECTION objects.Each CENA PDS data product f ile contains an ARRAY of records of CENA measurements in one orbit. Ea ch record is [truncated!, Please see actual data for full text]

This repository contains a homogeneous earthquake catalogue in Mw for the pre-1964 period, documenting 2,556 earthquakes that occurred in South America. It was compiled as part of the T4 catalogue of the SARA project (South America Risk Assessment). The moment magnitude (Mw) for these events was determined from various sources, including ISC-GEM (Storchak et al., 2013), CERESIS (1995), and national seismic databases. The dataset is provided in CSV format and includes details such as the source code, event date (Year, Month, Day, Hour, Minute, Second), maximum intensity, number of known Macroseismic Data Points (MDPs), epicentral coordinates (Latitude, Longitude), hypocentral depth (km), Mw and its associated uncertainty, and the method used for Mw determination.

References

Storchak, D.A., Di Giacomo D., Bondár I., Engdahl E.R., Harris J., Lee W.H.K., Villaseñor A. and Bormann P. (2013), Public Release of the ISC-GEM Global Instrumental Earthquake Catalogue (1900-2009), Seism. Res. Lett., 84, 5, 810-815, doi: 10.1785/0220130034.

CERESIS, Centro Regional de Sismología para América del Sur (1995). Catalogue for South America and he Caribbean prepared in the framework of GSHAP. File available and downloadable from http://www.seismo.ethz.ch/static/gshap/ceresis/.

Comprehensive dataset containing 27 verified Sara locations in RS with complete contact information, ratings, reviews, and location data.

Sara Petersen Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Comprehensive dataset containing 1 verified Sara locations in Arizona, United States with complete contact information, ratings, reviews, and location data.

Protein-Protein, Genetic, and Chemical Interactions for SARA (Drosophila melanogaster) curated by BioGRID (https://thebiogrid.org); DEFINITION: Smad anchor for receptor activation

This dataset provides information about the number of properties, residents, and average property values for Sara Circle cross streets in Santa Rosa Beach, FL.

Contents 1 Data set description 1.1 Data set overview 1.2 Parameters 1.3 Processing 1.4 Data 1.5 Ancillary data 1.6 Software 1.7 Media/Format 1.8 Review 1.9 Data quality 2 Confidence level note 2.1 Confidence level overview 2.2 Review 2.3 Data quality 1. Data set description 1.1. Data set overview SWIM is an ionmass analyser and hence the output data of SWIM sensor is basically ion counts in varoius energy, direction and mass bins. One full maesurement cycle of SWIM is 8s.The data coming from the sensor is being sorted by lookup tables and is being sorted into into two types of accumulation matrixes (the accumulation matrix and the accumulation scaling matrix) during one cycle of measurement. The accumulation matrix size changes depending on the binning parameters (energy, Deflection and mass bins).For details on the SWIM sensor of the SARA experiment and the data products, see the EAICD in the DOCUMENT directory. 1.2. Parameters The measured parameter is basically raw ion counts. 1.3. Processing No processing beyond unpacking has been applied to the telemetry data. 1.4. Data Each data product contains all data from one orbit. The data product contain housekeeping data as well as science data as scaling matrix(total counts) and accumulation matrix. SWIM data is archived using the storage format of PDS ARRAY of COLLECTION objects.Each SWIM PDS data product file contains an ARRAY of records of SWIM measurements in one orbit. Each record is described using a COLLECTION object.A PDS SWIM COLLECTION object groups all data related to one measurement:SWIM parameters (start time, compression mode, cycles of integration, etc.), reassembled housekeeping parameters in the header of the science data, the accumulation scaling matrix (counter data summed during a sampling period) and the accumulation matrix(event data integrated during a sampling period).If the binning parameters change within an orbit, the number of elements o tr [truncated!, Please see actual data for full text]

We previously demonstrated that MgrA, SarA, SarR, SarS, SarZ, and Rot bind at least three of the four promoters associated with genes encoding primary extracellular proteases in Staphylococcus aureus (Aur, ScpA, SspA/SspB, SplA-F). We also showed that mutation of sarA results in a greater increase in protease production, and decrease in biofilm formation, than mutation of the loci encoding any of these other proteins. However, these conclusions were based on in vitro studies. Thus, the goal of the experiments reported here was to determine the relative impact of the regulatory loci encoding these proteins in vivo. To this end, we compared the virulence of mgrA, sarA, sarR, sarS, sarZ, and rot mutants in a murine osteomyelitis model. Mutants were generated in the methicillin-resistant USA300 strain LAC and the methicillin-sensitive USA200 strain UAMS-1, which was isolated directly from the bone of an osteomyelitis patient during surgical debridement. Mutation of mgrA and rot limited virulence to a statistically significant extent in UAMS-1, but not in LAC, while the sarA mutant exhibited reduced virulence in both strains. The reduced virulence of the sarA mutant was correlated with reduced cytotoxicity for osteoblasts and osteoclasts, reduced biofilm formation, and reduced sensitivity to the antimicrobial peptide indolicidin, all of which were directly attributable to increased protease production in both LAC and UAMS-1. These results illustrate the importance of considering diverse clinical isolates when evaluating the impact of regulatory mutations on virulence and demonstrate the significance of SarA in limiting protease production in vivo in S. aureus.

Sara Textiles Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Plant Macrofossil. The data include parameters of plant macrofossil (population abundance) with a geographic _location of Louisiana, United States Of America. The time period coverage is from 30126 to 30105 in calendar years before present (BP). See metadata information for parameter and study _location details. Please cite this study when using the data.

Points features of pavilion locations at SARA Mission Reach project.Data interpreted from 2014 Google 6" orthoimagery (received through Bexar Metro 9-1-1 Network District acquisition). Data created and field-verified (using ESRI Collector App) October 2014.

Comprehensive dataset containing 1 verified Sara locations in AL with complete contact information, ratings, reviews, and location data.