Annual Resident Population Estimates, Estimated Components of Resident Population Change, and Rates of the Components of Resident Population Change; for the United States, States, Metropolitan Statistical Areas, Micropolitan Statistical Areas, Counties, and Puerto Rico: April 1, 2010 to July 1, 2019 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through March. // Note: Total population change includes a residual.

This data contains X-ray computed tomography (XCT) reconstructed slices of additively manufactured cobalt chrome samples produced with varying laser powder bed fusion (LPBF) processing parameters (scan speed and hatch spacing). A constant laser power of 195 W and a layer thickness of 20 µm were used. Unoptimized processing parameters created defects in these parts. The as-built CoCr disks were 40 mm in diameter and 10 mm in height, with no post-processing step (e.g. heat treatment or hot isostatic pressing) used.

Training and test-related data to accompany "Keyphrase Extraction for Technical Language Processing" by Alden Dima and Aaron Massey (in press). The subdirectories "keyphrase-extraction-jct-train" and "keyphrase-extraction-jct-test" contain a total of 1153 ThermoML files which are each associated with a corresponding Journal of Chemical Thermodynamics (JCT) article. These ThermoML files contain information about these papers in extensible markup language (XML) format including the title, authors, abstract, digital object identifier (DOI) and keywords.

Summary of simulation results that are used to generate figures in a paper titled "Performance Evaluation of Proximity Services and Wi-Fi for PublicSafety Mission Critical Voice Application". The paper was submitted to the special issue "Broadband Wireless Access for Rural and Remote Areas" of journal "Wireless Communications and Mobile Computing" on December 12, 2019.

ZIP Code Business Patterns (ZBP) is an annual series that provides economic data by ZIP Code. This table includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll for All Industries (NAICS 00) by 5-digit ZIP Code.

Small Area Income and Poverty Estimates: State and County

The U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program provides annual estimates of income and poverty statistics for all school districts, counties, and states. The main objective of this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs.

To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI).

The Public Use Microdata Sample (PUMS) for Puerto Rico (PR) contains a sample of responses to the Puerto Rico Community Survey (PRCS). The PRCS is similar to, but separate from, the American Community Survey (ACS). The PRCS collects data about the population and housing units in Puerto Rico. Puerto Rico data is not included in the national PUMS files. It is published as a state equivalent file and has a State FIPS code of “72”.

The American Community Survey (ACS) Public Use Microdata Sample (PUMS) contains a sample of responses to the ACS. The ACS PUMS dataset includes variables for nearly every question on the survey, as well as many new variables that were derived after the fact from multiple survey responses (such as poverty status).Each record in the file represents a single person, or, in the household-level dataset, a single housing unit. In the person-level file, individuals are organized into households, making possible the study of people within the contexts of their families and other household members.