Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Infection with toxin a-negative, toxin b-negative, binary toxin-positive clostridium difficile in a young patient with ulcerative colitis

Large clostridial toxin-negative, binary toxin-positive (A- B- CDT+) strains of Clostridium difficile are almost never associated with clinically significant C. difficile infection (CDI), possibly because such strains are not detected by most diagnostic methods. We report the isolation of an A- B- CDT+ ribotype 033 (RT033) strain of C. difficile from a young patient with ulcerative colitis and severe diarrhea