Cosmic-ray atmospheric cutoff energies of polar neutron monitors

Abstract The atmospheric cutoff, similarly to the geomagnetic cutoff, is the lower energy limit for cosmic ray particles that can reach a given location on the ground and be registered by a detector there, e.g., by a neutron monitor. It is caused by the decreasing intensity of a cosmic-ray cascade in the lower atmosphere. Although the geomagnetic cutoff is higher than atmospheric over the most of the Earth’s surface, the latter is dominant and therefore defines the neutron monitor count rate in the polar regions. The atmospheric cutoff decreases with the altitude, and this provides additional sensitivity of high-altitude polar neutron monitors to low-energy particles, mainly solar energetic protons during the so-called ground-level enhancement events. In this work, we quantitatively estimated the atmospheric cutoff energies for 21 polar neutron monitor stations in conditions without a significant solar energetic particle event. The cutoff value can be as low as about 300 MeV for protons (VOSTOK and DOMC/DOMB stations), which is notably lower than about 430 MeV at sea level. In addition to that, we estimated the worst case scenario of the strongest-ever observed ground-level enhancement event GLE#05, occurred on the 23rd of February, 1956, and showed that the atmospheric cutoff becomes as low as about 100 MeV. In other words, some neutron monitor stations can register particles with energies of even about 100 MeV during an exceptionally strong solar particle event. It is explained by the highly intensive and soft spectrum of the event in its early delayed phase

Reproducibility in the absence of selective reporting: An illustration from large‐scale brain asymmetry research

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes