The dissertation "The Thermodynamics and Hysteresis of Adsorption" by A. J. Brown, contains unique measurements of adsorption/desorption isotherms of Xenon, Krypton, and Carbon Dioxide in Vycor Glass. A particular hallmark of this set of isotherms is an extensive set of scanning isotherms of Xenon at 151 K, examining numerous trajectories inside the adsorption-desorption hysteresis loop. The isotherms were provided in tabular form in appendices of the dissertation, allowing for conversion to digital files without loss of fidelity.

Sample data and code for "Accurate localization microscopy by intrinsic aberration calibration", Craig R. Copeland, Craig D. McGray, B. Robert Ilic, Jon Geist, and Samuel M. Stavis, Nature Communications X, Y (2021). For use in MATLAB.

This project aims to create a comprehensive framework for generating radio frequency (RF) datasets, designing deep learning (DL) detectors, and evaluating their detection performance using both simulated and experimental test data. The proposed tools and techniques are developed in the context of dynamic spectrum use for the 3.5 GHz Citizens Broadband Radio Service (CBRS), but they can be utilized and expanded for standardization of machine learned spectrum awareness technologies and methods.

Round 5 Train DatasetThe data being generated and disseminated is the train data used to construct trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform text sentiment classification on English text. 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.

This database contains imaging and calibration data for phantoms contained in the NIST/NIBIB Phantom Lending Library (PLL). Description and access to the PLL can be found at https://www.nist.gov/programs-projects/nistnibib-medical-imaging-phanto… . Public analysis software written in Python can be found at https://github.com/MRIStandards/PhantomViewer .

This dataset contains information regarding the development of targeted GC-MS methods for forensic seized drug analysis. Included in this dataset are method parameter files, mass spectra, mass spectral databases, and retention time / retention index data.

Tabulations at 1 K intervals from 1 K to 6000 K of the partition function and standard-state isobaric heat capacity, entropy, and enthalpy for the 12 natural isotopologues of CO2, along with their standard uncertainties. Calculations performed with a partition function constructed from spectroscopic and theoretical data as described in the Appendix of the paper by A.H. Harvey, S.A. Tashkun, and E.W. Lemmon, to be submitted to J. Phys. Chem. Ref. Data. Note that the model does not account for dissociation of the CO2 molecule, making the results incomplete above approximately 3500 K.

This database gives hydrogen-deuterium exchange mass spectrometry (HDX-MS) data from measurements of three purified IgG1 glycoform samples, predominantly G0F, G2F, and SAF, in isolation and in complexation with the high-affinity receptor, Fc(gamma)RIa (CD64). The IgG1 antibody used in this study, aIL8hFc, is a murine-human chimeric IgG1, which inhibits IL-8 binding to human neutrophils.

Data set from peer-reviewed publication: A. J. Fleisher et al., Absolute 13C/12C Isotope Amount Ratio for Vienna Pee Dee Belemnite from Infrared Absorption Spectroscopy, Nature Physics. Measurements of isotope ratios are predominantly made with reference to standard specimens that have been characterized in the past. In the 1950s, the carbon isotope ratio was referenced to a belemnite sample collected by Heinz Lowenstam and Harold Urey in South Carolina?s Pee Dee region.

Data for D. A. Long, B. J. Reschovsky, F. Zhou, Y. Bao, T. W. LeBrun, and J. J. Gorman, "Electro-optic frequency combs for rapid interrogation in cavity optomechanics," Optics Letters Vol. 46, Issue 3, pp. 645-648 (2021), https://doi.org/10.1364/OL.405299