This Standard Reference Material (SRM) is intended for use as a primary calibration standard for the quantitative determination of aluminum. A unit of SRM 3101a consists of five 10 mL sealed borosilicate glass ampoules of an acidified aqueous solution prepared gravimetrically to contain a known mass fraction of aluminum. The solution contains nitric acid at a volume fraction of approximately 10 %, equivalent to an amount of substance concentration (molarity) of approximately 1.6 mol/L. This data is public in the Certificate of Analysis for this material.

This Standard Reference Material (SRM) is intended for use as a primary calibration standard for the quantitative determination of antimony. A unit of SRM 3102a consists of 50 mL of an acidified aqueous solution prepared gravimetrically to contain a known mass fraction of antimony in a high-density polyethylene bottle sealed in an aluminized bag.

This Standard Reference Material (SRM) is intended for use as a primary calibration standard for the quantitative determination of tellurium. A unit of SRM 3156 consists of five 10 mL sealed borosilicate glass ampoules of an acidified aqueous solution prepared gravimetrically to contain a known mass fraction of tellurium. The solution contains hydrochloric acid at a volume fraction of approximately 10 %, which is equivalent to an amount of substance concentration (molarity) of approximately 1.2 mol/L. This data is public in the Certificate of Analysis for this material.

This Standard Reference Material (SRM) is intended for use as a primary calibration standard for the quantitative determination of tungsten. A unit of SRM 3163 consists of 50 mL of an acidified aqueous solution prepared gravimetrically to contain a known mass fraction of tungsten in a high-density polyethylene bottle sealed in an aluminized bag.

The spreadsheet file reported herein provides centroid data, descriptive of deuterium uptake, for the Fab Fragment of NISTmAb (PDB: 5K8A) reference material, as measured by the bottom-up hydrogen-deuterium exchange mass spectrometry (HDX-MS) method. The protein sample was incubated in deuterium-rich solutions under uniform pH and salt concentrations between 3.6 degrees C and 25.4 degrees C for seven intervals ranging (0 to 14,400) s plus a control sample that simulates a Fab Fragment immersed for infinite time in D2O.

This tutorial provides mechanical drawings, electrical schematics, parts lists, STL files for 3D-printed parts, IGS files, and instructions for automated machining necessary for construction of a dual-protease, subzero, liquid chromatography system for hydrogen-deuterium exchange mass spectrometry. Electrical schematics for construction of a multi-zone temperature controller that regulate to ±0.1 oC are also included in this tutorial.

Round 1 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 1 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 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.

Round1 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.

Round 2 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.