The QIF PMI Report (QPR) software generates a spreadsheet from a QIF (Quality Information Framework) file containing Product and Manufacturing Information (PMI). QIF is a unified XML framework standard for computer-aided quality QIF systems, available free to all implementers. QIF enables the capture, use, and re-use of metrology-related information throughout the Product Lifecycle Management (PLM) and Product Data Management (PDM) domains. QIF was created by the Digital Metrology Standards Consortium.

Web calculator for polypeptide motion through nanopores. The calculation is done in the framework of conditional first passage times based on the Smoluchowski transport equation. These calculations are quite complex in general, but this calculator allows the piecewise construction of an energy landscape that reflects the average forces on a polymer confined in a nanopore based on its primary sequence. The calculator is written in HTML and javascript.

We investigated the influence of the state of wear of Charpy machine anvils on test results by performing impact tests on NIST specimens of three energy levels with a machine equipped with new anvils (compliant with both ASTM E23 and ISO 148-2) and worn anvils (anvil corner radii and distance outside ASTM tolerances, but within ISO tolerances).

The data used to generate the graphs in figures 2, 4, 5 and 6 of the paper "Evaluating Uncertainty of Nonlinear Microwave Calibrations from Regression Residuals". The full reference is D. F. Williams, B. Jamroz and J. D. Rezac, "Evaluating Uncertainty of Nonlinear Microwave Calibration Models With Regression Residuals," in IEEE Transactions on Microwave Theory and Techniques, vol. 68, no. 9, pp. 3776-3782, Sept. 2020, doi: 10.1109/TMTT.2020.3005170.

This repository contains all submissions made to the Mosaic Standards challenge from the period of the challenge opening through December 31st, 2019. The Mosaic Standards Challenge asked the microbiome research community to participate in determining the level of variation due to wet-lab protocols by sequencing a set of samples and providing the resulting files. Each participant ordered one or more kits, where each kit contained five fecal samples and two predetermined DNA mixtures.

Round 1 Test Dataset

This document identifies the NIST Cybersecurity Framework Subcategories that map closely to the potential mitigations within Advanced Metering Infrastructure (AMI), Distributed Energy Resources (DER), and Distribution Grid Management (DGM) threat scenarios in the NESCOR document. This mapping is useful in determining which NIST Cybersecurity Framework Subcategories are most relevant to addressing cyber risks in voltage regulation for the distribution system and is helpful in comparing DER and traditional grid environments.

This document provides details on the experiment and associated measurement files available for download in the dataset ?In Situ Thermography During Laser Powder Bed Fusion of a Nickel Superalloy 625 Artifact with Various Overhangs and Supports.? The measurements were acquired during the fabrication of a small nickel superalloy 625 (IN625) artifact using a commercial laser powder bed fusion (LPBF) system. The artifact consists of two half-arch features with increasing degrees of overhangs, from 5° to 85°, in increments of 10°.

One-minute averaged values and one-second instantaneous values for 2015 through 2018 for three grid-connected photovoltaic arrays on the NIST campus in Gaithersburg, Maryland USA. The arrays are built from monocrystalline silicon modules and range from 73 kW to 217 kW. Each array has a different tilt, orientation, and configuration. Irradiance, temperature, wind, and electrical measurements are recorded at each array.

SEDCORR is an open-source Python module designed to correct for the systematic energy deficits in atom probe mass spectra of electrically insulating samples. The assumption of the algorithm is that the mass spectrum for a dataset is conserved throughout the dataset and that any changes to the peak positions arise from an unknown slowly-fluctuating accelerating voltage. For computational speed, the unknown accelerating voltage is determined using a template matching FFT-based cross correlation method.