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Abstract. According to the valence asymmetry hypothesis, the left/right asymmetry of prefrontal cortex (PFC) activity is correlated with specific emotional responses to mental stress and personality traits. Here, we evaluated the relation between emotional state and asymmetry in PFC activity at rest by using near-infrared spectroscopy (NIRS). We measured spontaneous oscillation of oxyhemoglobin (oxy-Hb) concentrations in the bilateral PFC at rest in normal adults employing two-channel NIRS. In order to analyze left/right asymmetry of PFC activity at rest, we calculated the laterality index at rest (LIR) (see text). We investigated the correlation between the LIR and anxiety levels evaluated by the State-Trait Anxiety Inventory (STAI) test. We found that the right PFC was more active at rest than the left PFC, corresponding to a higher anxiety level measured by the STAI; that is, subjects with right-dominant activity at rest showed higher STAI scores, while those with leftdominant oxy-Hb changes at rest showed lower STAI scores. Aging had no significant effect on the relation. The present results obtained by NIRS are consistent with the valence asymmetry hypothesis. We emphasize NIRS may be a useful tool for objective assessment of anxiety levels.

In this paper, simulating a group fire in a densely inhabited area with weak small wooden buildings, we performed reduced scale model experiments to investigate flame merging. To study this phenomenon, a lot of experiments were performed using crib and liquid fuel. In this work, however two or more square propane porous burners are used, and the flame height, heat flux, and temperature distribution on the center axis of fires are measured. Consequently, the influence of the heat release rate, the number of fire sources and the distance between fire sources upon flame merging has been investigated.It is found that each of those parameters affected flame merging, although the number of fire sources seemed to be the most important parameter.

The aim of this study was to predict mental stress levels of aged people at rest from two-channel near-infrared spectroscopy (NIRS) data from the prefrontal cortex (PFC). We used the State-Trait Anxiety Inventory (STAI) for the mental stress index.We previously constructed a machine learning algorithm to predict mental stress level using two-channel NIRS data from the PFC in 19 subjects aged 20-24 years at rest (Sato et al., Adv Exp Med Biol 765:251-256, 2013). In the present study, we attempted the same prediction for aged subjects aged 61-79 years (10 women; 7 men). The mental stress index was again STAI. After subjects answered the STAI questionnaire, the NIRS device measured oxy- and deoxy-hemoglobin concentration changes during a 3-min resting state. The algorithm was formulated within a Bayesian machine learning framework and implemented by Markov Chain Monte Carlo. Leave-one-subject-out cross-validation was performed.Average prediction error between the actual and predicted STAI values was 5.27. Prediction errors of 12 subjects were lower than 5.0. Since the STAI score ranged from 20 to 80, the algorithm appeared functional for aged subjects also.