This data publication contains the mass spectrometry chemical characterization of microplastic and nanoplastic chemical analysis. The data from this study includes mass spectra of pure, mixed, and weathered microplastics and nanoplastics at high and low fragmentation, extracted ion chronograms, Kendrick mass defect plots, code, and the derived and processed data. The data analysis code (MATLAB 2022a*) used for unsupervised learning of cluster and compositional relationships is also included.

Provides data that will measure hunger and food security. It will provide data on food expenditure, access to food, and food quality and safety.

Data for the figures in the manuscript entitled "Quantum-limited optical time transfer for future geosynchronous links" first published as a preprint at https://arxiv.org/abs/2212.12541. Abstract: The combination of optical time transfer and optical clocks opens up the possibility of large-scale free-space networks that connect both ground-based optical clocks and future space-based optical clocks. Such networks promise better tests of general relativity, dark matter searches, and gravitational wave detection.

Data from controlled methane release of 10/29/2022

Data from peer-reviewed publication: A. J. Fleisher et al., Dual electro-optic frequency comb photonic thermometry, Optics Letters. We report a precision realization of photonic thermometry using dual-comb spectroscopy to interrogate a ?-phase-shifted fiber Bragg grating. We achieve read-out stability of 7.5 mK at 1 s and resolve temperature changes of similar magnitude?sufficient for most industrial applications.

This module for ns-3 implements the classes required to model a network architecture based on the O-RAN Alliance's specifications. These models include a Radio Access Network (RAN) Intelligent Controller (RIC) that is functionally equivalent to O-RAN's Near-Real Time (Near-RT) RIC, and reporting modules that attach to simulation nodes and serve as communication endpoints with the RIC in a similar fashion as the E2 Terminators in O-RAN.

This collection is comprised of multiple sets of experiments involving iPSCs with varying dosages of fluorescent light excitation. Samples were imaged every 2 minutes using phase-contrast microscopy for 20+ hours with or without fluorescence excitation. Each experiment was done on different days (i.e. exp0 vs exp1) but with triplicate wells (i.e. exp1-0, exp1-1, exp1-2). Additionally, data used to train our 2D U-Net and 3D U-Net models are included. Detailed information for each dataset can be found in Dataset_Information.xlsx.

The data in this record contains the physical and chemical vertical observational data from fixed mooring CHRP5 in the central basin of Lake Erie, Great Lakes region from 2022-05-18 through 2022-10-05. The approximate depth at CHRP5 is 15.3 m. Observations were collected at hourly or sub-hourly time intervals for water temperature and dissolved oxygen. The moorings are designed in a U-shape with a spar buoy and a subsurface buoy approximately 300 ft apart. The spar buoy has a surface expression float and holds the upper water column sensors.

NOAA-20 (N20/JPSS-1/J1) is the second satellite in the US NOAA latest generation Joint Polar Satellite System (JPSS). N20 was launched on November 18, 2017. In conjunction with the first US satellite in JPSS series, Suomi National Polar-orbiting Partnership (S-NPP) satellite launched on October 28, 2011, N20 form the new NOAA polar constellation. NOAA is responsible for all JPSS products, including SST from the Visible Infrared Imaging Radiometer Suite (VIIRS).

Round 13 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of object detection AIs trained both on synthetic image data build from Cityscapes and the DOTA_v2 dataset. 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 dataset consists of 128 AI models using a small set of model architectures.