Synthetic training and test datasets for experiments on deep generative modeling of noise time series. Consists of data for the following noise types: 1) band-limited thermal noise, i.e., bandpass filtered white Gaussian noise, 2) power law noise, including fractional Gaussian noise (FGN), fractional Brownian motion (FBM), and fractionally differenced white noise (FDWN), 3) generalized shot noise, 4) impulsive noise, including Bernoulli-Gaussian (BG) and symmetric alpha stable (SAS) distributions.

NFIMM is a software library written in C++ and runs on all the major computer platforms, for example, linux. It updates the header metadata for BMP and PNG image files while leaving the image data unchanged.

The image and the metadata to be updated is supplied by the NFIMM using-software:

It may be possible to use a mixture of known peptides run on a linear gradient to create a model that can be used to predict an unknown LC gradient of unknown samples based on deviation from the model. Data from RM 8321 can also be used to test other de novo search algorithms since it is a known mixture of 439 peptides. This data set consists of LC-MS/MS analysis of RM 8321 on a linear gradient of five varied lengths (30 min, 60 min, 90 min, 120 min, and 240 min), which can be used for modeling or testing de novo searching.

The files within this record represent the data shown in the Nature Physics article, "Strong parametric dispersive shifts in a statically decoupled two-qubit cavity QED system". Descriptions of this data are most detailed within the figure captions of the article. Please download and review the file "3027_README.txt" to learn more.

DyScO3 (DSO) serves as a substrate on which to grow epitaxial thin films with extraordinary materials physics. The film properties are determined by the biaxial in-plane strain due to DyScO3's slight lattice mismatch in comparison to common perovskite films. Hence, DyScO3 is an attractive substrate for materials studies, yet its highly anisotropic permittivity makes some measurements exceedingly difficult.

This repository contains two types of datasets: 4D-STEM data collected from a thermal annealing series of P3MEEMT films.

An experiment was set up at the University of Tennessee Knoxville (UTK) to test methods for estimating the cutting forces in real time within machine tools for any spindle speed, force profile, tool type, and cutting conditions. Before cutting, a metrology suite and instrumented tool holder were used to induce magnetic forces during spindle rotation, while on-machine vibrations, magnetic forces, and error motions were measured for various combinations of speeds and forces.

This dataset contains 1) the methane, ethane, ammonia, and water mixing ratio time series recorded at the Platteville Atmospheric Observatory site, 2) the hourly mean energy and agriculture apportioned methane mixing ratio time series, and 3) the atmospheric transport matrix H used for the Bayesian inversion analysis.

This dataset represents the results of calculations of atomic absorption spectra for the case of two-color EIT. We compare computation methods, specifically Gaussian sampling, to find that one sampling method converges to smooth transmittance curves in less time than the other. We also include some example scripts which generate and plot the figure data.

Here are included figures and other relevant data from the paper "Electro-Acoustic Nonlinear Signal Mixing" to be published in proceedings to The Device Research Conference.