Computer simulation of humanitarian scenarios: tools for training and field management in relief agencies

Computer simulation, a technology well advanced in military strategies and tactics, has been used for response to natural disasters. The authors argue that it should also be applied to the field of humanitarian action in armed conflict. Projected uses are: the management and planning of relief actions, public resource mobilization for humanitarian actions, and training personnel for violent work environments. How that can happen is shown with the example of a real relief management problem in the Sudan.

Simulation can be introduced in ways that are compatible with agencies’ needs, communication styles, and staff abilities. Several factors speak for it: many agencies routinely use computer applications that are flexible enough for simulation to be added seamlessly. Simulation will help agencies to add the power of analysis to the images that prompt humanitarian actions. And with violence and chaos continuing, simulation offers a technique around which to share expertise and training in new, networked partnerships.     

Stable isotope models to predict geographic origin and cultivation conditions of marijuana

Here we describe stable isotope based models using hydrogen and carbon isotope ratios to predict geographic region-of-origin and growth environment for marijuana, with the intent of applying these models to analyses of marijuana trafficking in the USA. The models were developed on the basis of eradication specimens and border specimens seized throughout the USA. We tested reliability of the geographic region-of-origin and growth environment models with a “blind” set of 60 marijuana eradication specimens obtained from counties throughout the USA. The two geographic region-of-origin model predictions were 60–67% reliable and cultivation environment model predictions were 86% accurate for the blind specimens. We demonstrate here that stable isotope ratio analysis of marijuana seizures can significantly improve our understanding of marijuana distribution networks and it is for that purpose that these models were developed.