The authors regret having incorrectly written in equation (7) that the fraction of surviving cells (SF) is obtained using the natural logarithm of the negative value of the number of lethal lesions L_f. The natural logarithm must be replaced by the exponential function as follows: [Formula presented] Although the equation is incorrectly written in the paper, its correct expression has been used in the results of the analysis shown in Figure 4. This error has no impact on the other results and conclusions of the paper. The authors would like to apologise for any inconvenience caused.

Low-cost muon detectors utilising cheap plastic scintillators and a limited number of individual silicon photomultipliers (SiPMs) offer a compelling approach to cheap experimental designs, provided the event localisation of a traversing particle can be accurately determined. In this theoretical work, we use Geant4 to simulate a diverse range of detector configurations, shapes and SiPM photosensors, predicting the light intensity received at a given SiPM. Testing a range of methods to localise muon events we determine that machine learning techniques outperform analytic models, and of these, a simple gradient boosted framework is the most reliably accurate localisation technique for our simulated scintillators. We find that a simple square scintillator outperforms other geometries and that AI performs, when applied to this shape, with a linear relationship between the positional accuracy of the event recovery and the average distance between photosensors around the detector perimeter.

This Special Report presents a description of Geant4-DNA user applications dedicated to the simulation of track structures (TS) in liquid water and associated physical quantities (e.g., range, stopping power, mean free path.). These example applications are included in the Geant4 Monte Carlo toolkit and are available in open access. Each application is described and comparisons to recent international recommendations are shown (e.g., ICRU, MIRD), when available. The influence of physics models available in Geant4-DNA for the simulation of electron interactions in liquid water is discussed. Thanks to these applications, the authors show that the most recent sets of physics models available in Geant4-DNA (the so-called "option4" and "option 6" sets) enable more accurate simulation of stopping powers, dose point kernels, and W-values in liquid water, than the default set of models ("option 2") initially provided in Geant4-DNA. They also serve as reference applications for Geant4-DNA users interested in TS simulations.

We report on the recent progress within the Geant4 electromagnetic physics subpackages. Several new interfaces and models recently introduced are already used in LHC applications and may be useful for any type of simulation. Significant developments were carried out to improve the user interface, develop models of single and multiple scattering, and validate high energy models. Part of these developments are included in the Geant4 10.2 release and the full set are available in the new version 10.3 of December, 2016.