qPCR results for Vitellogenin. This dataset is associated with the following publication: Armstrong, B., J. Lazorchak , K. Jensen , H. Haring , M.E. Smith, R. Flick , D. Bencic , and A. Biales. Reproductive effects in fathead minnows (Pimphales promelas) following a 21 d exposure to 17α-ethinylestradiol. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 144(1): 366-373, (2015).

The global summaries data set contains a monthly (GSOM) resolution of meteorological elements (max temp, snow, etc) from 1763 to present with updates weekly. The major parameters are: monthly mean maximum, mean minimum and mean temperatures; monthly total precipitation and snowfall; departure from normal of the mean temperature and total precipitation; monthly heating and cooling degree days; number of days that temperatures and precipitation are above or below certain thresholds; and extreme daily temperature and precipitation amounts. The primary source data set source is the Global Historical Climatology Network (GHCN)-Daily Data set. The global summaries data set also contains a yearly (GSOY) resolution of meteorological elements. See associated resources for more information. This data is not to be confused with "GHCN-Monthly", "Annual Summaries" or "NCDC Summary of the Month". There are unique elements that are produced globally within the GSOM and GSOY data files. There are also bias corrected temperature data in GHCN-Monthly, which will not be available in GSOM and GSOY. The GSOM and GSOY data set is going to replace the legacy DSI-3220 and expand to include non-U.S. (a.k.a. global) stations. DSI-3220 only included National Weather Service (NWS) COOP Published, or "Published in CD", sites.

The outputs of EURO-EXPERT include academic publications, CULTEXP - the first multilingual and cross-jurisdictional database on cultural expertise, data visualisation of in-court and out-of-court cultural expertise, a toolkit for the use of cultural expertise, and publications for the general public. This dataset is the EURO-EXPERT data summary for Italy.

The Government has published the Business Plan Quarterly Data Summaries (QDS) The QDS are designed to fit on a single page to provide a quarterly snapshot on how each department is spending its budget, the results it has achieved and how it is deploying its workforce. The QDS follows commitments made at Budget 2011 and the Written Ministerial Statement on Business Plans. Their primary purpose is to make more of the management information currently held by government available to members of the public on a regular basis. This information is not audited and the quality and accuracy of the data needs to dramatically improve. However, over time with improvements in data quality and timeliness the public will be able to judge the performance of each department in a meaningful and understandable manner. We intend for an annual version of this information to be formally laid in Parliament in the Annual Report and Accounts for July 2011/12 onwards. The information is presented in excel format to allow the information to be presented in a re-usable format. The QDS template is the same for all departments, though many of the individual indicators are unique to the department (especially input and impact indicators). This is the first time Government has published this kind of information, and while this is a good start, there is room for improvement. Before using this data people should ensure they take full note of the caveats noted in each Department’s measurement annex and treat with necessary caution. At the moment, people should not be using this data to make direct comparisons between departments for several reasons. Firstly, the business of each department is unique and it does not make sense to compare some measures across all departments. Secondly, many of the measures are not directly comparable because they do not have common definitions, time periods, or data collection processes. We will be updating regularly the QDS each quarter with the next publication following in October 2011.

This is the latest statistical publication of linked HES (Hospital Episode Statistics) and DID (Diagnostic Imaging Dataset) data held by the Health and Social Care Information Centre. The HES-DID linkage provides the ability to undertake national (within England) analysis along acute patient pathways to understand typical imaging requirements for given procedures, and/or the outcomes after particular imaging has been undertaken, thereby enabling a much deeper understanding of outcomes of imaging and to allow assessment of variation in practice. This publication aims to highlight to users the availability of this updated linkage and provide users of the data with some standard information to assess their analysis approach against. The two data sets have been linked using specific patient identifiers collected in HES and DID. The linkage allows the data sets to be linked from April 2012 when the DID data was first collected; however this report focuses on patients who were present in either data set for the period April 2015-February 2016 only. For DID this is provisional 2015/16 data. For HES this is provisional 2015/16 data. The linkage used for this publication was created on 06 June 2016 and released together with this publication on 07 July 2016.

This is the Summary Data used in the Early Achievers Dashboard. This dashboard displays aggregated DCYF Early Achievers data, including counts of participating providers and provider ratings, to demonstrate statewide progress of the Early Achievers quality recognition initiative. The data is updated monthly and provides a ‘snapshot’ of Early Achievers participant data as of the indicated date. *Link to the Early Achievers Dashboard https://www.dcyf.wa.gov/practice/oiaa/reports/early-learning-dashboards/early-achievers-data-dashboard

The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. With data from the 2007 Commodity Flow Survey and additional sources, FAF version 3 (FAF3) provides estimates for tonnage, value, and domestic ton-miles by region of origin and destination, commodity type, and mode for 2007, the most recent year, and forecasts through 2040. Also included are state-to-state flows for these years plus 1997 and 2002, summary statistics, and flows by truck assigned to the highway network for 2007 and 2040.

These tabular data are the summarization of climate related variables within catchments of the Chesapeake Bay watershed at the 1:24,000 scale using the xstrm methodology. Variables being counted as climate related include temperature and precipitation by both annual and monthly timesteps. Outputs include tabular comma-separated values files (CSVs) and parquet formatted files for the local catchment and network summaries linked to the National Hydrography Dataset Plus High-Resolution (NHDPlus HR) catchments by NHDPlus ID. Local catchments are defined as the single catchment within which the data are summarized. Network summaries are summaries for each of the local catchments and their respective network-connected upstream or downstream catchments for select variables. The summarized data tables are structured as a single column representing the catchment id values (i.e. NHDPlus ID) and the remaining columns consisting of the summarized variables. The downstream network summary type ...

This page provides data for the 3rd Grade Reading Level Proficiency performance measure.The dataset includes the student performance results on the English/Language Arts section of the AzMERIT from the Fall 2017 and Spring 2018. Data is representive of students in third grade in public elementary schools in Tempe. This includes schools from both Tempe Elementary and Kyrene districts. Results are by school and provide the total number of students tested, total percentage passing and percentage of students scoring at each of the four levels of proficiency.

The performance measure dashboard is available at 3.07 3rd Grade Reading Level Proficiency.Additional InformationSource: Arizona Department of EducationContact: Ann Lynn DiDomenicoContact E-Mail: Ann_DiDomenico@tempe.govData Source Type: Excel/ CSVPreparation Method: Filters on original dataset: within "Schools" Tab School District [select Tempe School District and Kyrene School District]; School Name [deselect Kyrene SD not in Tempe city limits]; Content Area [select English Language Arts]; Test Level [select Grade 3]; Subgroup/Ethnicity [select All Students] Remove irrelevant fields; Add Fiscal YearPublish Frequency: Annually as data becomes availablePublish Method: ManualData Dictionary

Electric scooter trips taken during the 2020 Chicago pilot program, summarized by census tract for the entire 2020 season. For more information on the pilot, see https://www.chicago.gov/scooters.

For privacy reasons, some Census Tracts (accounting for fewer than 0.2% of trips) corresponding to very-low-frequency combinations have been removed. Note that some other Census Tract values may be blank due to limitations in the source data or being outside Chicago.

These tabular data are the summarization of human related variables within the Chesapeake Bay watershed using the xstrm methodology bringing these data to the 1:24,000 scale. Variables being counted as human related include agriculture, barriers, road density and road/stream crossing data. Outputs include tabular comma-separated values files (CSVs), and parquet formatted files for both the local catchment and network summaries linked to the National Hydrography Dataset Plus High-Resolution (NHDPlus HR) catchments by NHDPlus ID. Local catchments are defined as the single catchment the data is summarized within. Network accumulation summaries were completed for each of the local catchments and their network connected upstream and/or downstream catchments. The summarized data tables are structured as a single column representing the catchment id values (ie. nhdplusid) and the remaining columns consisting of the summarized variables. Additionally, for a full description of the variables included within these summaries see xstrm_nhdhr_human_chesapeake_baywide_datadictionary.csv in the attached files. The xstrm local summary methodology takes either raster or point data as input then summarizes those data by "zones" (hereafter referred to as catchment(s)), in this case the NHDPlus HR catchments. The network summaries then take the results from the local summaries and calculates the desired network summary statistic for the local catchment and its respective upstream or downstream catchments. As a note concerning use of these data, any rasters summarized within this process only had their cells included within a catchment if the center of the raster cell fell within the catchment boundary. However, the resolution of the input raster data for these summaries was considered to provide completely adequate coverage of the summary catchments using this option and given computing power limitations. If a confirmed complete coverage of a catchment is desired (even if a raster cell only is minimally included within the catchment) then it is recommended to rerun the xstrm summary process with the "All Touched" option set to "True". These data were updated in September of 2024 where several variables unnecessary to the use of the data summaries were removed, incorrectly calculated area variables and all dependent variables were corrected, and several new variables were added to the dataset. Further information on the Xstrm summary process can be found at the Xstrm software release pages: Xstrm: Wieferich, D.J., Williams, B., Falgout, J.T., Foks, N.L. 2021. xstrm. U.S. Geological Survey software release. https://doi.org/10.5066/P9P8P7Z0. Xstrm Local: Wieferich, D.J., Gressler B., Krause K., Wieczorek M., McDonald, S. 2022. xstrm_local Version-1.1.0. U.S. Geological Survey software release. https://doi.org/10.5066/P98BOGI9.

CA Head of Household Recipients between 16 and 24.

This folder contains 3 .csv files which contain all the observations for the suite of major ion and nutrient constituents for the Heart River Basin. These files contain the water-quality observations for the statistical summary tables in the report cited in this data release (Tatge and others, 2021).The allsiteinfo.table.csv file can be used to cross reference the sites with the main report (Tatge and others, 2021). Tatge, W.S., Nustad, R.A., and Galloway, J.M., 2021, Evaluation of Salinity and Nutrient Conditions in the Heart River Basin, North Dakota, 1970-2020: U.S. Geological Survey Scientific Investigations Report 2021-XXXX, XX p.

The data sets are annual summaries of the untreated Ottawa River water, the Treated water leaving each drinking water purification plant (Britannia and Lemieux Island) plus the Central Distribution System for each calendar year. These data sets are summaries of selected key physical, chemical, microbiological and radiological parameters.

Full water quality summaries are available online at: http://www.ottawa.ca/en/env_water/water_sewer/water_wells/wells/city_wells/index.html.

Accuracy: There are no known errors with this data report

Update Frequency: Annual

Contact: Drinking Water Services, Water Quality Assurance Unit

This package contains data sets for development (Section dev) and testing (Section test) of machine translation of sentences from summaries of medical articles between Czech, English, French, German, Hungarian, Polish, Spanish and Swedish. Version 2.0 extends the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.

Under the new QDS framework departments’ spending data is published every quarter; to show the taxpayer how the Government is spending their money. The QDS grew out of commitments made in the 2011 Budget and the Written Ministerial Statement on Business Plans. For the financial year 2012/13 the QDS has been revised and improved in line with Action 9 of the Civil Service Reform Plan to provide a common set of data that will enable comparisons of operational performance across Government so that departments and individuals can be held to account. Q1 2012/13 is the first set of this new data collection and comprises of different categories and subsets. As collection proceeds, we expect to be able to make meaningful comparisons on what Departments are spending.

The QDS breaks down the total spend of the department in three ways: by Budget, by Internal Operation and by Transaction. At the moment this data is published by individual departments in Excel format, however, in the future the intention is to make this data available centrally through an online application.

Over time we will be making further improvements to the quality of the data and its timeliness. We expect that with time this process will allow the public to better understand the performance of each department and government operations in a meaningful way.

The QDS template is the same for all departments, though the individual detail of grants and policy will differ from department to department. In using this data: 1. People should ensure they take full note of the caveats noted in each Department’s return. 2. As the improvement of the QDS is an ongoing process data quality and completeness will be developed over time and therefore necessary caution should be applied to any comparative analysis undertaken.

Departmental Commentary

The Cabinet Office departmental family includes the Civil Service Commission. The figures for the Government Procurement Service are not included in the figures for Quarter 1.

Information from the TCEQ monthly waste receipts summary report form submitted by receivers of hazardous and Industrial Class 1 waste. It contains the receiver's registration number, the received date, waste code, quantity received, who shipped the waste and how it was handled.

List of footnotes, notes, and source information for NHIS Adult Summary Statistics. Each row of this dataset contains the accompanying text for a footnote found in the NHIS Adults Summary Statistics Dataset.

This submission includes publicly available data extracted in its original form. Please reference the Related Publication listed here for source and citation information If you have questions about the underlying data stored here, please contact the USDA. If you have questions or recommendations related to this metadata entry and extracted data, please contact the CAFE Data Management team at: climatecafe@bu.edu. "View summaries of each year's recalls including total number and number of pounds recalled." [Quote from https://www.fsis.usda.gov/food-safety/recalls-public-health-alerts/annual-recall-summaries]