This Standard Reference Material (SRM) is intended for use as an analytical standard of known potassium (K) and chloride (Cl-) content. This lot of potassium chloride (KCl) was prepared to ensure a material of high purity and homogeneity and has been assayed after drying at 500 °C. A unit of SRM 999c consists of a single glass bottle containing 30 g of the material. This data is public in the Certificate of Analysis for this material.

Standard Reference Material-1721: Southern Oceanic Air. Ambient Nominal Amount of Substance Fraction for Carbon Dioxide, Methane & Nitrous Oxide. This Standard Reference Material (SRM) is a primary gas mixture for which the amount-of-substance fraction, expressed as concentration, may be related to secondary working standards. This SRM is intended for the calibration of instruments used for ambient carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) determinations and for other applications. This data is public in the Certificate of Analysis for this material.

This Standard Reference Material (SRM) is intended for use as an analytical standard of known purity. It is intended primarily for use in the calibration and standardization of procedures for potassium (K) and chloride (Cl-) determinations employed in clinical analysis, including those using ion-selective electrodes, and for routine critical evaluation of the daily working standards used in these procedures. This lot of potassium chloride (KCl) was prepared to ensure a material of high purity and homogeneity and has been assayed after heating at 110 degrees C to 120 degrees C.

A comparison of the expanded uncertainty for certified values of iodine in food matrix CRMs. The CRMS were found by searching The European Virtual Institute for Speciation Analysis (EVISA) database using the terms "Iodine" and "Certified" in the Material category. The uncertainties are expanded uncertainties at approximately 95% confidence.

All the data in this project are generated running Density Functional (DFT) simulation either on NIST computer clusters of through our collaborators at University of Florida. The final data consist in relaxed atomic structures and corresponding energetic, mechanical, electronic and phonon properties. The metadata consist in the initial and relaxed structures, the description of the code, of the k points and of all the parameters used in running the simulations (energy or real space cutoff, type of minimization, occupation, etc.).

The Micronutrients Measurement Quality Assurance Program (MMQAP) was coordinated by the Chemical Sciences Division and supported measurement technology for selected fat- and water-soluble vitamins and carotenoids in human serum. This program was initiated in 1984 by the National Cancer Institute Division of Cancer Prevention and Control to ensure the long-term reliability of the measurements made while studying the possible cancer chemoprevention roles of these compounds.

The Manufacturing Cost Guide is a tool that estimates the costs that US manufacturers face and can be used to help gauge the potential returns on manufacturing industry research projects through cost reductions. These costs are grouped into various standardized categories such as the North American Industry Classification System (NAICS) and the Standard Occupational Classification (SOC) system along with other non-standardized costs.

The tool can be used to answer questions such as:

Round 3 Training DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 2 Test DatasetThe data being generated and disseminated is the test data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 2 Holdout DatasetThe data being generated and disseminated is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.