The containment properties of alpha particles during the slowing-down process in an axisymmetric tokamak reactor are studied by using Monte-Carlo calculations, in which the pitch-anglescattering effects are included. The loss of alpha particles during slowing-down is found to be safely negligible in a pure DT plasma, but increases proportionally to the effective charge number of the plasma and cannot be ignored in a highly contaminated plasma (Z e ff > 4), compared with the loss of 3.5-MeV particles.

Background: Functional near-infrared spectroscopy (fNIRS) is a new noninvasive neuroimaging technology that detects both oxyhemoglobin hemodynamics (HbO) and deoxy-hemoglobin hemodynamics (HbR), but there is no assessment approach that emphasizes the merits of fNIRS. New method: Based on fNIRS, we established an indicator system named the Area-Under-Curve-based Indicator System (AUCIS) to estimate the effect reliability of brain responses. Evaluating the positive and negative responses for HbO and HbR can better explain, to some extent, the comprehensive physiological mechanism of oxygen delivery to and extraction in the brain. Moreover, we also established a reliability coefficient, named AUC’ α, to assess the robustness of within-subject condition effects. Results and Comparison: To validate the AUCIS, we used a simulation-based HRF signal and an open database and compared the performance with other general indicators. The AUCIS showed a greater relative sensitivity and robustness, which can be explained in terms of oxygen delivery and extraction based on the negative and positive responses of HbO and HbR.