Vaporization of sodium from a partially molten chondritic material

In order to examine vaporization behavior of sodium for partially molten chondritic materials, heating experiments were carried out using two starting materials prepared from the Etter (L5) chondrite (grain-sizes : sample A, φ torr, and heating duration up to 160min. Chemical analyses and petrographical examinations were carried out for starting materials and run products. The rates of vaporizations for sodium were estimated for partial melts (degree of melting=11-34%) at 1200-1400℃. Differences in the vaporization rates for the partially molten charges obtained from different starting materials were not detected clearly at the same temperatures. Systematically different trends of sodium vaporization rate are found between those obtained in this work and those previously reported for total melts (at 1450-1600℃) from similar starting materials (TSUCHIYAMA et al., 1981). It appears that the vaporization mechanism of Na is basically the same in the temperature range from 1200 to 1600℃ for partially to completely molten charges

Predictability of conversation partners

Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information theoretic method to the spatiotemporal data of cell-phone locations, [C. Song et al. Science 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one's conversation partners is defined as the degree to which one's next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to some extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual's predictability is correlated with the position in the static social network derived from the data. Individuals confined in a community - in the sense of an abundance of surrounding triangles - tend to have low predictability, and those bridging different communities tend to have high predictability.Comment: 38 pages, 19 figure