In this 2019 article published in Molecules, Palmieri et al. demonstrate their ability to use nine cannabinoids, a specific analytical method, and multivariate analysis—without any other identifying information—to identify the retailer of 161 hemp samples from four retailers. Highlighting the fact that simply using analyses of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) "to extrapolate the phytochemical composition of hemp" may be insufficient in some cases, the researchers turn to high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS) and partial least squares discriminant analysis (PLS-DA) to identify hemp sample origins. The authors note that using their techniques, "92% of the hemp samples were correctly classified by the cannabinoid variables in both fitting and cross-validation." They conclude "that a simple chemical analysis coupled with a robust chemometric method could be a powerful tool for forensic purposes."
This is a University of Washington-created course that is released on the edX platform. The self-paced four-week course is designed to help learners to better understand the "type of characteristics and skills needed for cybersecurity jobs and to provide a realistic outlook on what they really need to add to their 'toolkits'—a set of skills that is constantly evolving, not all technical, but fundamentally rooted in problem-solving." The course is free to take, with a Verified Certificate of completion available for $99. The course requires on average two to five hours a week of effort. Access to the class begins October 21, 2019.