Project documentation and demonstrations processing OSCAL (the Open Security Controls Assessment Language).

The files in this repository can be used to generate the complete set of figures in the paper "An algorithm to identify vapor-liquid-liquid equilibria from vapor-liquid equilibria". The zip file, when expanded, includes a conda environment to populate the dependencies, and a set of python scripts. Running make_figures.py will regenerate all the figures, demonstrating how to use the algorithm.

These four data files contain datasets from an interlaboratory comparison that characterized a polydisperse five-population bead dispersion in water. A more detailed version of this description is available in the ReadMe file (PdP-ILC_datasets_ReadMe_v1.txt), which also includes definitions of abbreviations used in the data files. Paired samples were evaluated, so the datasets are organized as pairs associated with a randomly assigned laboratory number.

The compartment fire test was conducted on the 9.1 m x 6.1 m steel-concrete composite floor, located in the south-central bay of the two-story steel gravity frame two bays by three bays in plan. The test floor assembly was designed and constructed to achieve a 2-hour fire-resistance rating per American Society for Testing and Materials (ASTM) standard E119. The fire-exposed composite slab was reinforced with the steel wire mesh mat (60 mm2/m) equivalent to the minimum code-prescribed steel reinforcement for shrinkage and temperature crack control under normal conditions.

The library multicomplex is an implementation of multicomplex algebra in C++ to allow for higher-order derivatives of numerical functions. Many (though not all) mathematical functions are implemented, allowing for calculation of derivatives (straight and mixed) to approximately numerical precision, which is difficult or impossible to achieve in conventional double precision

teqp is a library written in C++ that allows for calculation of numerical derivatives of thermodynamic equations of state with respect to the independent variables with numerical differentiation tools. No hand-written derivatives are required, and the computational speed is competitive with, or better than, the results from hand-written derivatives in low-level programming languages.

Direct Analysis in Real Time Mass Spectrometry (DART-MS) is an analytical chemistry technology that is being increasingly employed in forensic applications. This form of mass spectrometry rapidly yields rich structural information about an analyte with minimal sample preparation. The challenge with DART-MS data, much like other data generated with high throughput technologies, lies in the data interpretation. This is especially true when the analyzed samples are multi-component mixtures like seized drug evidence.

CMRG v1.00 of a small variant benchmark and structural variant benchmark focused on 273 challenging medically relevant genes for the Genome in a Bottle (GIAB) sample HG002 (aka Ashkenazi son). These benchmarks were generated from a trio-based hifiasm v0.11 (https://doi.org/10.1038/s41592-020-01056-5) diploid assembly of HG002 using PacBio HiFi reads for HG002 for assembly and partitioning into phased haplotypes using Illumina reads for the parents, HG003 and HG004.

Automated particle analysis (SEM/EDS) data from samples known to have been exposed to gunshot residue and from samples occasionally mistaken for gunshot residue - like brake dust and fireworks. The dataset consists of analyses of 30 discrete samples: 12 from sampling automobiles ("brake dust"), 10 from sampling fireworks ("sparklers" and "spinners" and "roman candles"), 8 from shooter's left or right hands. The analysis configuration meta-data for each analysis are contained in the "configuration.txt" and "script.py" files.

Python code for analyzing optical 2D spectroscopy data using linear prediction from singular value decomposition. Included as supplemental information with a publication on this topic. Includes scripts and associated data to generate the figures in the paper.