This table contains 32 series, with data for years 1961 - 1983 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (32 items: Canada; Amherst; Nova Scotia; New Glasgow; Nova Scotia; Charlottetown; Prince Edward Island ...), Average weekly earnings (1 items: Average weekly earnings ...), Seasonal adjustment (2 items: Unadjusted; Seasonally adjusted ...).

The statistic represents the average U.S. refiner acquisition cost of composite crude oil between 1985 and 2011. In 2000, this figure stood at around 28.26 U.S. dollars per barrel. According to the source, nominal U.S. dollars reflect the buying power in the year in which the transaction occurred; not adjusted to remove the effect of changes in the purchasing power of the dollar.

Graph and download economic data for Dow Jones Composite Average (DJCA) from 2015-07-31 to 2025-07-30 about composite, stock market, average, and USA.

United States - Dow Jones Composite Average was 13824.82000 Index in July of 2025, according to the United States Federal Reserve. Historically, United States - Dow Jones Composite Average reached a record high of 14373.96000 in November of 2024 and a record low of 2195.30000 in March of 2009. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Dow Jones Composite Average - last updated from the United States Federal Reserve on August of 2025.

Massachusetts students led the way in composite ACT scores in the United States in 2021, with an average composite score of **** points out of 36. Nevada students had the lowest average composite score, with **** points. What is the ACT? The American College Test, or ACT, is one of the leading college and university entrance exams in the United States. The ACT tests reading, grammar, science, and math, as well as an optional writing supplement. Each section of the test is scored on a scale of 1 to 36, whereby test takers earn 1 point for every correct answer, and do not lose any points for wrong answers. The final score for each test section is then averaged to find the composite score, which is also scored between 1 and 36. College entrance exams The other main college entrance exam in the U.S. is the Scholastic Assessment Test, or SAT, which has a maximum score of 2400 (although the average score is about 1060). The SAT tests math, evidence-based reading and writing, and has an optional essay supplement as well. College entry exams like the SAT and ACT are used by universities to determine which applicants they accept, and more selective schools, such as the Ivy League, usually have higher requirements when looking at test scores.

United States Index: Dow Jones: Composite Average data was reported at 8,314.030 02Jan1934=39.57 in Oct 2018. This records a decrease from the previous number of 8,810.240 02Jan1934=39.57 for Sep 2018. United States Index: Dow Jones: Composite Average data is updated monthly, averaging 602.875 02Jan1934=39.57 from Jan 1953 (Median) to Oct 2018, with 790 observations. The data reached an all-time high of 8,810.240 02Jan1934=39.57 in Sep 2018 and a record low of 101.360 02Jan1934=39.57 in Sep 1953. United States Index: Dow Jones: Composite Average data remains active status in CEIC and is reported by Dow Jones. The data is categorized under Global Database’s United States – Table US.Z015: Dow Jones: Indexes.

This statistic represents the average weight of plastic and polymer composites in U.S. and Canadian-built light vehicles between 2009 and 2019. In 2019, the weight of plastic and polymer composites in the average light vehicle assembled here amounted to *** pounds per vehicle, accounting for some *** percent of the total vehicle weight.

Explore the progression of average salaries for graduates in Composite Materials Engineering from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Composite Materials Engineering relative to other fields. This data is essential for students assessing the return on investment of their education in Composite Materials Engineering, providing a clear picture of financial prospects post-graduation.

Diluted-Average-Shares Time Series for Shanghai Pret Composites. Shanghai Pret Composites Co., Ltd. engages in the research and development, production, sale, and service of polymer and composite materials in China. It offers modified polyolefin materials, ABS, polycarbonate alloy, and nylon material products for use in automotive interior and exterior decoration, electronic electrical, and military aerospace material applications; and LCP resin, LCP film, and LCP fiber materials for use in 5G high-frequency high-speed communication materials, high-frequency electronic connectors, acoustic wires, and military aerospace materials. Shanghai Pret Composites Co., Ltd. was founded in 1993 and is based in Shanghai, China.

The Earth Observations Group (EOG) is producing a version 1 suite of average radiance composite images using nighttime data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB).

Prior to averaging, the DNB data is filtered to exclude data impacted by stray light, lightning, lunar illumination, and cloud-cover. Cloud-cover is determined using the VIIRS Cloud Mask product (VCM). In addition, data near the edges of the swath are not included in the composites (aggregation zones 29-32).

Temporal averaging is done on a monthly and annual basis. The version 1 series of monthly composites has not been filtered to screen out lights from aurora, fires, boats, and other temporal lights. However, the annual composites have layers with additional separation, removing temporal lights and background (non-light) values.

The version 1 products span the globe from 75N latitude to 65S. The products are produced in 15 arc-second geographic grids and are made available in geotiff format as a set of 6 tiles. The tiles are cut at the equator and each span 120 degrees of latitude. Each tile is actually a set of images containing average radiance values and numbers of available observations.

In the monthly composites, there are many areas of the globe where it is impossible to get good quality data coverage for that month. This can be due to cloud-cover, especially in the tropical regions, or due to solar illumination, as happens toward the poles in their respective summer months. Therefore, it is imperative that users of these data utilize the cloud-free observations file and not assume a value of zero in the average radiance image means that no lights were observed.

The version 1 monthly series is run globally using two different configurations. The first excludes any data impacted by stray light. The second includes these data if the radiance vales have undergone the stray-light correction procedure (Reference). These two configurations are denoted in the filenames as "vcm" and "vcmsl" respectively. The "vcmsl" version, that includes the stray-light corrected data, will have more data coverage toward the poles, but will be of reduced quality. It is up to the users to determine which set is best for their applications. The annual versions are only made with the “vcm” version, excluding any data impacted by stray light.

Filenaming convention: The version 1 composite products have 7 filename fields that are separated by an underscore "_". Internal to each field there can be an additional dash separator "-". These fields are followed by a filename extension. The fields are described below using this example filename:

SVDNB_npp_20140501-20140531_global_vcmcfg_v10_c201502061154.avg_rade9

Field 1: VIIRS SDR or Product that made the composite "SVDNB" Field 2: satellite name "npp" Field 3: date range "20140501-20140531" Field 4: ROI "global" Field 5: config shortname "vcmcfg" Field 6: version "v10" is version 1.0 Field 7: creation date/time Extension: avg_rade9

The annual products can have other values for the config shortname (Field 5). They are: "vcm-orm" (VIIRS Cloud Mask - Outlier Removed) This product contains cloud-free average radiance values that have undergone an outlier removal process to filter out fires and other ephemeral lights. "vcm-orm-ntl" (VIIRS Cloud Mask - Outlier Removed - Nighttime Lights) This product contains the "vcm-orm" average, with background (non-lights) set to zero. "vcm-ntl" (VIIRS Cloud Mask - Nighttime Lights) This product contains the "vcm" average, with background (non-lights) set to zero.

Data types/formats: To reach the widest community of users, files are delivered in compressed tarballs, each containing a set of 2 geotiffs. Files with extensions "avg_rade9" contain floating point radiance values with units in nanoWatts/cm2/sr. Note that the original DNB radiance values have been multiplied by 1E9. This was done to alleviate issues some software packages were having with the very small numbers in the original units. Files with extension "cf_cvg" are integer counts of the number of cloud-free coverages, or observations, that went in to constructing the average radiance image. Files with extension “cvg” are integer counts of the number of coverages or total observations available (regardless of cloud-cover).

Credit: When using the data please credit the product generation to the Earth Observation Group, Payne Institute for Public Policy.

The Earth Observations Group (EOG) at National Oceanic and Atmospheric Administration (NOAA)/National Geophysical Data Center (NGDC) is producing a version 1 suite of average radiance composite images using nighttime data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB). Prior to averaging, the DNB data is filtered to exclude data impacted by stray light, lightning, lunar illumination, and cloud-cover. Cloud-cover is determined using the VIIRS Cloud Mask product (VCM). In addition, data near the edges of the swath are not included in the composites (aggregation zones 29-32). Temporal averaging is done on a monthly and annual basis. The version 1 series of monthly composites has not been filtered to screen out lights from aurora, fires, boats, and other temporal lights. However, the annual composites have layers with additional separation, removing temporal lights and background (non-light) values. The version 1 products span the globe from 75N latitude to 65S. The products are produced in 15 arc-second geographic grids and are made available in geotiff format as a set of 6 tiles. The tiles are cut at the equator and each span 120 degrees of latitude. Each tile is actually a set of images containing average radiance values and numbers of available observations. The dataset is the night light annual composite in year of 2015. The dataset is a KML file which requires the Google earth to visualize. For other monthly and annual basis night light geotiff datasets (up to Sep 2017), please download at https://www.ngdc.noaa.gov/eog/viirs/download_dnb_composites.html#NTL_2015 Citation: the Earth Observation Group, NOAA National Geophysical Data Center

United States US Composite: Index: Dow Jones Transportation Average data was reported at 13,639.750 NA in Apr 2025. This records a decrease from the previous number of 14,746.160 NA for Mar 2025. United States US Composite: Index: Dow Jones Transportation Average data is updated monthly, averaging 10,464.600 NA from Jul 2013 (Median) to Apr 2025, with 142 observations. The data reached an all-time high of 17,618.630 NA in Nov 2024 and a record low of 6,249.880 NA in Aug 2013. United States US Composite: Index: Dow Jones Transportation Average data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: US Composite (NYSE, NASDAQ): Dow Jones: Monthly.

US Composite: Index: Dow Jones Composite Average Total Return data was reported at 32,138.880 NA in Apr 2025. This records a decrease from the previous number of 33,312.100 NA for Mar 2025. US Composite: Index: Dow Jones Composite Average Total Return data is updated monthly, averaging 18,259.895 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 36,237.720 NA in Nov 2024 and a record low of 8,179.630 NA in May 2012. US Composite: Index: Dow Jones Composite Average Total Return data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: US Composite (NYSE, NASDAQ): Dow Jones: Monthly.

Explore the progression of average salaries for graduates in Polymer Composite from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Polymer Composite relative to other fields. This data is essential for students assessing the return on investment of their education in Polymer Composite, providing a clear picture of financial prospects post-graduation.

The presence of fecal bacteria in irrigation waters is well documented in causing human and animal illnesses, with the potential for antibiotic-resistant pathogens to increase the seriousness of these infections. Approaches to sampling fecal and antibiotic-resistant bacteria (ARB) in irrigation waters used in raw food production require standardization to quantify and discern potential spatiotemporal trends in antibiotic-resistant bacteria. Composite sampling is widely used to reduce the cost and time of processing samples while estimating spatial or temporal variation in contaminant concentrations. The objectives of this work were to evaluate the spatial variation in generic and ARB in several irrigation ponds and assess the effectiveness of composite sampling in estimating the average of individual samples. In a grid-like fashion, five irrigation ponds were sampled for generic and antibiotic-resistant E. coli and total coliforms using the Colilert Quanti-Tray/2000 system with and without tetracycline and cefotaxime added. Individual samples were composited in sample sets including all samples, only bank samples, and only interior samples. Coefficients of variations in general were high (> 100%) for generic bacteria and higher for ARB (140%−290%). Concentrations of all measured bacteria were lower in the pond interior locations than the banks. The percentage of tetracycline-resistant E. coli varied among ponds from averages of 0% to 23%. No cefotaxime-resistant E. coli were detected in any of the ponds whereas cefotaxime-resistant total coliforms were detected at each site. The average percentage of cefotaxime-resistant total coliforms varied from 1.1 to 13.8% among ponds. E. coli concentrations in composite samples did not significantly differ from either the mean or median of the individual sample sets in 89% and 83% of cases, respectively, indicating composite sampling to be effective in capturing spatial variation of both generic and ARB. Results of this work can be used to aid in the development of better strategies for surveilling antibiotic resistance in aquatic environments.

Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using Landsat 8 satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of 1) developed, 2) vegetated, 3) unvegetated fractional covers and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the years 2014-2018. Additionally, multi-year average values of vegetated fractional cover and its standard deviation are provided for the coastal wetlands of the contiguous United States based on the National Wetland Inventory delineation. Finally, a UVVR based on the annually-averaged vegetated fractional cover is also provided for the same extent.

As a new way of reporting treatment effect, the restricted mean time in favor (RMT-IF) of treatment measures the net average time the treated have had a less serious outcome than the untreated over a specified time window. With multiple outcomes of differing severity, this offers a more interpretable and data-efficient alternative to the prototypical restricted mean (event-free) survival time. To facilitate its adoption in actual trials, we develop simple approaches to power and sample size calculations and implement them in user-friendly R programs. In doing so we model the bivariate outcomes of death and a nonfatal event using a Gumbel–Hougaard copula with component-wise proportional hazards structures, under which the RMT-IF estimand is derived in closed form. In a standard set-up for censoring, the variance of the nonparametric effect-size estimator is simplified and computed via a hybrid of numerical and Monte Carlo integrations, allowing us to compute the power and sample size as functions of component-wise hazard ratios. Simulation studies show that these formulas provide accurate approximations in realistic settings. To illustrate our methods, we consider designing a new trial to evaluate treatment effect on the composite outcomes of death and cancer relapse in lymph node-positive breast cancer patients, with baseline parameters calculated from a previous study.

The Day Night Band (DNB), from the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Joint Polar-orbiting Satellite System (JPSS) satellites, provides global daily measurements of nocturnal visible and near-infrared light that are suitable for Earth system science and applications studies. The VIIRS Nighttime Lights Monthly Cloud-Free Composite is produced using average radiance composite images and excludes any data impacted by stray light. There are many areas of the globe where it is impossible to get good quality data coverage for that month. This can be due to cloud-cover, especially in the tropical regions, or due to solar illumination, as happens toward the poles in their respective summer months. Therefore, when used for analysis, it is imperative that users of these data utilize the cloud-free observations file (band-2) and not assume a value of zero in the average radiance image (band-1) means that no lights were observed.Geographic CoverageGlobal from 75N to 65SCoverage is affected by the length of day during different times of the year. For example, summer time in the northern hemisphere will have less nighttime coverage due to longer days.Temporal CoverageMonthly from January 2014 - February 2024BandsBand-1: Monthly average radianceUnits: (avg_rade9h) nW/cm2/srBand-2: Cloud free observations per monthUnits: DaysCoordinate Reference SystemSource images are stored in Geographic WGS84 (EPSG:4326) and transformed on-the-fly to Web Mercator (EPSG:3857)Spatial Resolution15 arc second (~500m at the Equator)VIIRS Nighttime Lights product generation is credited to the Earth Observation Group, Payne Institute for Public Policy.

Mean composite anomalies in surface and average 100 first meters of EKE for upwelling or downwelling IEKWs events. Anomalies refer here as the difference between the mean over the first 20 days of each individual selected event and the long-term mean (1993-2018). The bar of differences (upwelling/downwelling vs CR-long run) in % are averaged in the first 20 or 40 days. The error bars (low and high) denote the confidence intervals at 95% based on Student t test.

The Dow Jones Composite Index finished the year 2024 at 13,391.71 points, an increase compared to the previous year. Even with the economic effects of the global coronavirus (COVID-19) pandemic, 2021 had the highest point of the index in the past two decades. What is Dow Jones Composite Index? The Dow Jones Composite Index is one of the indices from the Dow Jones index family. It is composed of 65 leading U.S. companies: 30 stocks forming the Dow Jones Industrial Average index, 20 stocks from the Dow Jones Transportation index and 15 stocks from the Dow Jones Utility Average index. Importance of stock indices A stock market index shows an average performance of companies from a given section of the market. It is usually a weighted average, meaning that such factors as price of companies or their market capitalization are taken into consideration when calculating the index value. Stock indices are very useful for the financial market participants, as they instantly show the sentiments prevailing on a given market. They are also commonly used as a benchmark against portfolio performance, showing if a given portfolio has outperformed, or underperformed the market.