Mobile Crowdsourcing for High-Accuracy Thunderhead Prediction

A system and method are disclosed to predict location of a thunderhead using crowd sourced mobile technology. The system comprises multiple smartphones enabled to detect relative wind speed, direction and pressure gradients. The crowd-sourced wind movements determine thermal rise locations that are fed into weather models. The system software uses this information to provide targeted emergency weather alerts with pinpoint precision. The resulting thunderhead discoverability is valuable to any group that provides or relies on accurate weather predictions

The dual-system approach is a useful heuristic but does not accurately describe behavior

We argue that the dual-system approach and, particularly, the default-interventionist framework favored by De Neys unnecessarily constrains process models, limiting their range of application. In turn, the accommodations De Neys makes for these constraints raise questions of parsimony and falsifiability. We conclude that the extent to which processes possess features of system 1 versus system 2 must be tested empirically

Small x nonlinear evolution with impact parameter and the structure function data

The nonlinear Balitsky-Kovchegov equation at small x is solved numerically, incorporating impact parameter dependence. Confinement is modeled by including effective gluon mass in the dipole evolution kernel, which regulates the splitting of dipoles with large sizes. It is shown, that the solution is sensitive to different implementations of the mass in the kernel. In addition, running coupling effects are taken into account in this analysis. Finally, a comparison of the calculations using the dipole framework with the inclusive data from HERA on the structure functions F2 and FL is performed.Comment: 19 pages, 11 figures. Minor revision. One reference added, two figures update