A code repository and accompanying data for incorporating imperfect theory into machine learning for improved prediction and explainability. Specifically, it focuses on the case study of the dimensions of a polymer chain in different solvent qualities. Jupyter Notebooks for quickly testing concepts and reproducing figures, as well as source code that computes the mean squared error as a function of dataset size for various machine learning models are included.For additional details on the data, please refer to the README.md associated with the data.

SolDet is an object-oriented package for solitonic feature detection in absorption images of Bose-Einstein condensate. with wider use for cold atom image analysis. Featured with classifier, object detector, and Mexican hat metric methods. Technical details are explained in https://arxiv.org/abs/2111.04881.

This research software package contains Python code to execute experiments on deep generative modeling of classical random process models for noise time series. Specifically, it includes Pytorch implementations of two generative adversarial network (GAN) models for time series based on convolutational neural networks (CNNs): WaveGAN, a 1-D CNN model, and STFT-GAN, a 2-D CNN model. In addition, there are methods for generating and evaluating noise time series defined several by classical random process models.

Lipid nanoparticles (LNPs) were prepared as described (https://doi.org/10.1038/s42003-021-02441-2) using the lipids DLin-KC2-DMA, DSPC, cholesterol, and PEG-DMG2000 at mol ratios of 50:10:38.5:1.5. Four sample types were prepared: LNPs in the presence and absence of RNA, and with LNPs ejected into pH 4 and pH 7.4 buffer after microfluidic assembly. To prepare samples for imaging, 3 ?L of LNP formulation was applied to holey carbon grids (Quantifoil, R3.5/1, 200 mesh copper).

Almanac API - Ranking by Geography ID within the Nation

This API is designed to find the rankings by geography within the state for a specific metric (population or household) and rank (any of the metrics from provider, demographic, technology or speed). The results are the top ten and bottom ten records within the state for the particular geography type and my area rankings. Additionally we include +/- 5 rankings from the 'my' area rank.

This API is designed to find the rankings by any geography ID within the nation with a specific census metric (population or household) and ranking metric (any of the metrics from provider, demographic, technology or speed). The results are the top ten and bottom ten rankings within the nation for the particular geography type and my area rankings include +/- 5 rankings from the my area rank.

This API is designed to find the rankings by any geography type within the state with a specific census metric (population or household) and ranking metric (any of the metrics from provider, demographic, technology or speed). Only the top ten and bottom ten rankings would be returned through the API if the result set is greater than 500; otherwise full ranking list be returned.

This API is designed to find the rankings by any geography type within the nation with a specific census metric (population or household) and ranking metric (any of the metrics from provider, demographic, technology or speed). Support for full list of rankings by nation is not allowed for geography types (e.g., county, census place, usf) so only the top ten and bottom ten rankings would be returned through the API.

The Broadband Provider API searches for all providers with a specified name.