These images, videos, and tables show experimental data, where single lines of viscoelastic inks were extruded into moving viscoelastic support baths. Lines were printed at varying angles relative to the camera, such that videos and images captured the side of horizontal lines, cross-sections of horizontal lines, and the side of vertical lines. Metadata including pressure graphs, programmed speeds, toolpaths, and rheology data are also included.

The data are for a combination of static and dynamic scattering techniques that show there are measurable direct and indirect interactions between soft lipid vesicles in concentrated solutions.

Implementation of the Metaschema modeling language in Java, providing support for Java code, schema, and documentation generation based on one or more Metaschema model definitions.Code is developed in Java and shared via GitHub's USNISTGOV organization.

Source code associated with the Inverted Library Search Algorithm (ILSA) for identifying mixture components using is-CID mass spectra. This source code is frozen to accompany the manuscript titled "Updates to the Inverted Library Search Algorithm for mixture analysis" by Moorthy et. al.

This Python software package provides functionality for inference of the initial state of a Hidden Markov Model (HMM), when we have access to permutations of the underlying states. We provide both analytical calculations to compute the probability of correct inference, and functionality for Monte Carlo computations. Further details are provided in arxiv:xxxx.xxxxxx.

Examples of adaptive measurement protocols using optimal Bayesian experiment design. This dataset supports "Simplified algorithms for adaptive experiment design in parameter estimation", arXiv 2202.08344 and submitted to Physical Review Applied. The calculations use python package optbayesexpt, which is available from https://github.com/usnistgov/optbayesexpt. The software applies to measurements of parameters in nonlinear parametric models.

This project produces synthetic datasets of spectrum sharing simulation results (I/Q data, metadata, and KPIs).

This tool is a Python client that can interact with the NIST Entropy Source Validation Test System.

In the field of tissue engineering, 3D scaffolds and cells are often combined to yield constructs that are used as therapeutics to repair or restore tissue function in patients. Viable cells are often required to achieve the intended mechanism of action for the therapy, where the live cells may build new tissue or may release factors that induce tissue regeneration. Thus, there is a need to reliably measure cell viability in 3D scaffolds as a quality attribute of a tissue-engineered medical product.

The Computer Forensics Tool Testing Program is a project in The Software and Systems Division supported by the Special Programs Office and the Department of Homeland Security. Through the Cyber Security Division Cyber Forensics project, the Department of Homeland Security's Science and Technology partners with the NIST CFTT project to provide forensic tool testing reports to the public.