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

Data set on the storage duration effects on oxidative stress biomarkers in the tissues of exercised mice.

This dataset presents the data of our research about the effect of sample freezing on oxidative stress biomarkers (thiobarbituric acid reactive substances, protein carbonyl derivatives, total antioxidant capacity, superoxide dismutase and catalase activity) in different tissues (heart, skeletal muscles, brain) of mice in response to a maximum exercise. The markers were quantified in fresh and frozen tissues (1 to 6 months) in control and exercised animals

Modified version of the PCAT-A10 tool for the evaluation of primary care Evaluación de la atención primaria, versión modificada del instrumento PCAT-A10

Altres ajuts: Este trabajo ha sido parcialmente financiado por el CIBER de Epidemiología y Salud Pública.Objective: To evaluate the measurement characteristics of the Spanish and Catalan versions of the 10-Item Primary Care Assessment Tool for adults (PCAT-A10), shortened from the original Primary Care Assessment Tool (PCAT), with a new mental health item. Design: Cross-sectional observational study. Location: The city of Barcelona. Participants: Of the 3,496 people over 14 years of age from the representative random sample of the Barcelona population, from the 2016-17 Barcelona Health Survey, those who declared they had a family doctor, and had visited a specialist at some time in their lives, and had answered more than 50% of PCAT-A10 items were selected (n = 3,107). Main measurements: Item descriptive analysis, analysis of internal consistency, corrected item - total correlation, of the PCAT-A10 index and the 10 items that make it up. Three scenarios for non-response to treatment were analysed: substitution by 0, by the intermediate value, and excluding people who did not answer any item. Results: The PCAT-A10 index obtained Cronbach alphas of 0.73, 0.79, and 0.85 in the three mentioned scenarios, correlation item total corrected between 0.41 and 0.66, and 20.8% non-responses to the mental health item. Conclusions: The new version of PCAT-A10 has a high reliability with a higher response in the mental health item compared to the previous version